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  • MPI Ethno. Forsch.  (389)
  • Birmingham, UK : Packt Publishing  (358)
  • Birmingham, UK : Packt Pub.  (31)
  • Python (Computer program language)  (274)
  • Web site development  (122)
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  • MPI Ethno. Forsch.  (389)
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Years
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Keywords
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  • 1
    Online Resource
    Online Resource
    Web app development made simple with Streamlit : a web developer's guide to effortless web app... development, deployment, and scalability (2024)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781835085936 , 1835085938 , 9781835086315
    Language: English
    Pages: 1 online resource (350 pages) , illustrations
    Parallel Title: Erscheint auch als
    DDC: 005.7/2
    Keywords: Web site development ; Web applications ; Sites Web ; Développement ; Applications Web
    Abstract: Unlock the full potential of Streamlit, mastering web app development from setup to deployment with practical guidance, advanced techniques, and real-world examples Key Features Identify and overcome web development challenges, crafting dedicated application skeletons using Streamlit Understand how Streamlit's widgets and components work to implement any kind of web app Manage web application development and deployment with ease using the Streamlit Cloud service Purchase of the print or Kindle book includes a free PDF eBook Book Description This book is a comprehensive guide to the Streamlit open-source Python library and simplifying the process of creating web applications. Through hands-on guidance and realistic examples, you'll progress from crafting simple to sophisticated web applications from scratch. This book covers everything from understanding Streamlit's central principles, modules, basic features, and widgets to advanced skills such as dealing with databases, hashes, sessions, and multipages. Starting with fundamental concepts like operation systems virtualization, IDEs, development environments, widgets, scripting, and the anatomy of web apps, the initial chapters set the groundwork. You'll then apply this knowledge to develop some real web apps, gradually advancing to more complex apps, incorporating features like natural language processing (NLP), computer vision, dashboards with interactive charts, file uploading, and much more. The book concludes by delving into the implementation of advanced skills and deployment techniques. By the end of this book, you'll have transformed into a proficient developer, equipped with advanced skills for handling databases, implementing secure login processes, managing session states, creating multipage applications, and seamlessly deploying them on the cloud. What you will learn Develop interactive web apps with Streamlit and deploy them seamlessly on the cloud Acquire in-depth theoretical and practical expertise in using Streamlit for app development Use themes and customization for visually appealing web apps tailored to specific needs Implement advanced features including secure login, signup processes, file uploaders, and database connections Build a catalog of scripts and routines to efficiently implement new web apps Attain autonomy in adopting new Streamlit features rapidly and effectively Who this book is for This book is for Python programmers, web developers, computer science students, and IT enthusiasts with a foundation in Python (or any programming language) who have a passion for creating visually appealing applications. If you already know how to write programs, this book will help you evolve into an adept web application developer skilled at converting command-line tools into impressive, cloud-hosted applications.
    Note: Includes index
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Data labeling in machine learning with Python : modern ways to prepare the labeled data for training and fine-tuning ML and AI models (2023)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781804613788 , 1804613789 , 9781804610541
    Language: English
    Pages: 1 online resource (398 pages) , illustrations
    Parallel Title: Erscheint auch als
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Machine learning ; Computer programming ; Python (Langage de programmation) ; Apprentissage automatique ; Programmation (Informatique) ; computer programming
    Abstract: Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labeling Key Features Generate labels for regression in scenarios with limited training data Apply generative AI and large language models (LLMs) to explore and label text data Leverage Python libraries for image, video, and audio data analysis and data labeling Purchase of the print or Kindle book includes a free PDF eBook Book Description Data labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today's data-driven world, mastering data labeling is not just an advantage, it's a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you'll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data. What you will learn Excel in exploratory data analysis (EDA) for tabular, text, audio, video, and image data Understand how to use Python libraries to apply rules to label raw data Discover data augmentation techniques for adding classification labels Leverage K-means clustering to classify unsupervised data Explore how hybrid supervised learning is applied to add labels for classification Master text data classification with generative AI Detect objects and classify images with OpenCV and YOLO Uncover a range of techniques and resources for data annotation Who this book is for This book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.
    Note: Includes index
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Learning Python networking : a complete guide to build and deploy strong networking capabilities using Python 3.7 and Ansible (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789952445 , 1789952441
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Computer networks ; Management ; Client/server computing ; Electronic books ; Electronic books ; local
    Abstract: Achieve improved network programmability and automation by leveraging powerful network programming concepts, algorithms, and tools Key Features Deal with remote network servers using SSH, FTP, SNMP and LDAP protocols. Design multi threaded and event-driven architectures for asynchronous servers programming. Leverage your Python programming skills to build powerful network applications Book Description Network programming has always been a demanding task. With full-featured and well-documented libraries all the way up the stack, Python makes network programming the enjoyable experience it should be. Starting with a walk through of today's major networking protocols, through this book, you'll learn how to employ Python for network programming, how to request and retrieve web resources, and how to extract data in major formats over the web. You will utilize Python for emailing using different protocols, and you'll interact with remote systems and IP and DNS networking. You will cover the connection of networking devices and configuration using Python 3.7, along with cloud-based network management tasks using Python. As the book progresses, socket programming will be covered, followed by how to design servers, and the pros and cons of multithreaded and event-driven architectures. You'll develop practical clientside applications, including web API clients, email clients, SSH, and FTP. These applications will also be implemented through existing web application frameworks. What you will learn Execute Python modules on networking tools Automate tasks regarding the analysis and extraction of information from a network Get to grips with asynchronous programming modules available in Python Get to grips with IP address manipulation modules using Python programming Understand the main frameworks available in Python that are focused on web application Manipulate IP addresses and perform CIDR calculations Who this book is for If you're a Python developer or a system administrator with Python experience and you're looking to take your first steps in network programming, then this book is for you. If you're a network engineer or a network professional aiming to be more productive and efficient in networking programmability and automation then this book would serve as a useful resource. Basic knowledge of Python is assumed.
    Note: Previous edition published: 2015. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789958096/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    WordPress 5 complete : build a beautiful and feature-rich websites from scratch (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789538533 , 178953853X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Seventh edition.
    Keywords: WordPress (Electronic resource) ; Web site development ; Web publishing ; Blogs ; Electronic books ; Electronic books ; local
    Abstract: An in-depth and comprehensive take on WordPress, covering everything about the platform such as WordPress posts, pages, themes, plugins, and more. Key Features Get up to date with the latest WordPress 5.0 (Bebo) and all its new features Beginner-friendly layout and advice you can apply from day one with loads of screenshots and examples Enrich your development experience with the new block-based editor Gutenberg Book Description Back in the day, when you wanted to launch a new website, you either had to learn web programming yourself or hire a professional who would take care of the whole process for you. Nowadays, with WordPress, anyone can build an optimized site with the least amount of effort possible and then make it available to the world in no time. Here, in the seventh edition of the book, we are going to show you how to build great looking and functional websites using WordPress. The new version of WordPress ? 5.0 ? comes with a few important changes, and we tell you all about how to use them effectively. From crafting content pages using the block editor, and customizing the design of your site, through to making sure it's secure, we go through it all. The book starts by introducing WordPress and teaching you how to set it up. You are then shown how to create a blog site, start writing content, and even use plugins and themes to customize the design of the site and add some unique elements to set it apart. If you want to get more in-depth, we also show you how to get started creating your own themes and plugins. Finally, we teach you how to use WordPress for building non-blog websites. By the end of the book, you will be sufficiently skilled to design high-quality websites and will be fully familiar with the ins and outs of WordPress. What you will learn Learn to adapt your plugin with the Gutenberg editor Create content that is optimized for publication on the web Craft great looking pages and posts with the use of block editor Structure your web pages in an accessible and clear way Install and work with plugins and themes Customize the design of your website Upload multimedia content, such as images, audio, and video easily and effectively Develop your own WordPress plugins and themes Use WordPress to build websites that serve purposes other than blogs Who this book is for The ideal target audience for this book would be PHP developers who have some basic knowledge of working with WordPress and who want to get a comprehensive pract...
    Note: Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789532012/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    Mastering OpenCV 4 with Python : a practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7 (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789349757 , 1789349753
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: OpenCV (Computer program language) ; Computer vision ; Python (Computer program language) ; Image processing ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python Apply machine learning and deep learning techniques with TensorFlow, Keras, and PyTorch Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn Handle files and images, and explore various image processing techniques Explore image transformations, including translation, resizing, and cropping Gain insights into building histograms Brush up on contour detection, filtering, and drawing Work with Augmented Reality to build marker-based and markerless applications Work with the main machine learning algorithms in OpenCV Explore the deep learning Python libraries and OpenCV deep learning capabilities Create computer vision and deep lear...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 1, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789344912/?ar
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    Online Resource
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  • 6
    Online Resource
    Online Resource
    Mastering geospatial development with QGIS 3.x : an in-depth guide to becoming proficient in spatial data analysis using QGIS 3.4 and 3.6 with Python (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788994873 , 1788994876
    Language: English
    Pages: 1 online resource (1 volume) , illustrations, maps
    Edition: Third edition.
    Keywords: Geographic information systems ; Computer programs ; Geodatabases ; Computer programs ; Cartography ; Computer programs ; Geospatial data ; Data processing ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Go beyond the basics and unleash the full power of QGIS 3.4 and 3.6 with practical, step-by-step examples Key Features One-stop solution to all of your GIS needs Master QGIS by learning about database integration, and geoprocessing tools Learn about the new and updated Processing toolbox and perform spatial analysis Book Description QGIS is an open source solution to GIS and widely used by GIS professionals all over the world. It is the leading alternative to proprietary GIS software. Although QGIS is described as intuitive, it is also, by default, complex. Knowing which tools to use and how to apply them is essential to producing valuable deliverables on time. Starting with a refresher on the QGIS basics and getting you acquainted with the latest QGIS 3.6 updates, this book will take you all the way through to teaching you how to create a spatial database and a GeoPackage. Next, you will learn how to style raster and vector data by choosing and managing different colors. The book will then focus on processing raster and vector data. You will be then taught advanced applications, such as creating and editing vector data. Along with that, you will also learn about the newly updated Processing Toolbox, which will help you develop the advanced data visualizations. The book will then explain to you the graphic modeler, how to create QGIS plugins with PyQGIS, and how to integrate Python analysis scripts with QGIS. By the end of the book, you will understand how to work with all aspects of QGIS and will be ready to use it for any type of GIS work. What you will learn Create and manage a spatial database Get to know advanced techniques to style GIS data Prepare both vector and raster data for processing Add heat maps, live layer effects, and labels to your maps Master LAStools and GRASS integration with the Processing Toolbox Edit and repair topological data errors Automate workflows with batch processing and the QGIS Graphical Modeler Integrate Python scripting into your data processing workflows Develop your own QGIS plugins Who this book is for If you are a GIS professional, a consultant, a student, or perhaps a fast learner who wants to go beyond the basics of QGIS, then this book is for you. It will prepare you to realize the full potential of QGIS.
    Note: Previous edition published: 2016. - Description based on online resource; title from title page (Safari, viewed May 1, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788999892/?ar
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    Online Resource
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  • 7
    Online Resource
    Online Resource
    Building serverless microservices in Python : a complete guide to building, testing, and deploying microservices using serverless computing on AWS (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789533422 , 1789533422
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Cloud computing ; Electronic books ; Electronic books ; local
    Abstract: A practical guide for developing end-to-end serverless microservices in Python for developers, DevOps, and architects. Key Features Create a secure, cost-effective, and scalable serverless data API Use identity management and authentication for a user-specific and secure web application Go beyond traditional web hosting to explore the full range of cloud hosting options Book Description Over the last few years, there has been a massive shift from monolithic architecture to microservices, thanks to their small and independent deployments that allow increased flexibility and agile delivery. Traditionally, virtual machines and containers were the principal mediums for deploying microservices, but they involved a lot of operational effort, configuration, and maintenance. More recently, serverless computing has gained popularity due to its built-in autoscaling abilities, reduced operational costs, and increased productivity. Building Serverless Microservices in Python begins by introducing you to serverless microservice structures. You will then learn how to create your first serverless data API and test your microservice. Moving on, you'll delve into data management and work with serverless patterns. Finally, the book introduces you to the importance of securing microservices. By the end of the book, you will have gained the skills you need to combine microservices with serverless computing, making their deployment much easier thanks to the cloud provider managing the servers and capacity planning. What you will learn Discover what microservices offer above and beyond other architectures Create a serverless application with AWS Gain secure access to data and resources Run tests on your configuration and code Create a highly available serverless microservice data API Build, deploy, and run your serverless configuration and code Who this book is for If you are a developer with basic knowledge of Python and want to learn how to build, test, deploy, and secure microservices, then this book is for you. No prior knowledge of building microservices is required.
    Note: Description based on online resource; title from title page (Safari, viewed May 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789535297/?ar
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  • 8
    Online Resource
    Online Resource
    Drupal 8 module development : build modules and themes using the latest version of Drupal 8 (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789807868 , 1789807867
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Drupal (Computer file) ; Web sites ; Authoring programs ; Web site development ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Learn to create and customize impressive Drupal 8 modules to extend your website's functionalities Key Features Explore a plethora of Drupal 8 APIs and get the best out of them using the power of PHP coding Learn to implement efficient data management and data security by creating dedicated modules for it. Stay up to date with the changes introduced in the new Drupal 8 releases Book Description Drupal 8 comes with a release cycle that allows for new functionality to be added at a much faster pace. However, this also means code deprecations and changing architecture that you need to stay on top of. This book updates the first edition and includes the new functionality introduced in versions up to, and including 8.7. The book will first introduce you to the Drupal 8 architecture and its subsystems before diving into creating your first module with basic functionality. You will work with the Drupal logging and mailing systems, learn how to output data using the theme layer and work with menus and links programmatically. Then, you will learn how to work with different kinds of data storages, create custom entities, field types and leverage the Database API for lower level database queries. You will further see how to introduce JavaScript into your module, work with the various file systems and ensure the code you write works on multilingual sites. Finally, you will learn how to programmatically work with Views, write automated tests for your functionality and also write secure code in general. By the end, you will have learned how to develop your own custom module that can provide complex business solutions. And who knows, maybe you'll even contribute it back to the Drupal community. What you will learn Develop Drupal 8 modules that do all the things you want Master numerous Drupal 8 sub-systems and APIs in the process Model, store, manipulate and process data to serve your purposes Display data and content in a clean and secure way using the Drupal 8 theme system Test your business logic to prevent regressions Stay ahead of the curve and write code following the current best practices Who this book is for The primary target of this book is Drupal developers who want to learn how to write modules and develop in Drupal 8. It is also intended for Drupal site builders and PHP developers who have basic Object Oriented Programming skills. A little bit of Symfony experience is helpful but not mandatory.
    Note: Previous edition published: 2017. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789612363/?ar
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  • 9
    Online Resource
    Online Resource
    Python machine learning cookbook : over 100 recipes to progress from smart data analytics to deep learning using real-world datasets (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789800753 , 1789800757
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features Learn and implement machine learning algorithms in a variety of real-life scenarios Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn Use predictive modeling and apply it to real-world problems Explore data visualization techniques to interact with your data Learn how to build a recommendation engine Understand how to interact with text data and build models to analyze it Work with speech data and recognize spoken words using Hidden Markov Models Get well versed with reinforcement learning, automated ML, and transfer learning Work with image data and build systems for image recognition and biometric face recognition Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is w...
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789808452/?ar
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    Online Resource
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  • 10
    Online Resource
    Online Resource
    Hands-on unsupervised learning with Python : implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789349276 , 1789349273
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Artificial intelligence ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Discover the skill-sets required to implement various approaches to Machine Learning with Python Key Features Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more Build your own neural network models using modern Python libraries Practical examples show you how to implement different machine learning and deep learning techniques Book Description Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images. By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges. What you will learn Use cluster algorithms to identify and optimize natural groups of data Explore advanced non-linear and hierarchical clustering in action Soft label assignments for fuzzy c-means and Gaussian mixture models Detect anomalies through density estimation Perform principal component analysis using neural network models Create unsupervised models using GANs Who this book is for This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789348279/?ar
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  • 11
    Online Resource
    Online Resource
    Hands-on data science for marketing : improve your marketing strategies with machine learning using Python and R (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789348828 , 178934882X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Marketing ; Data processing ; Machine learning ; Marketing research ; Python (Computer program language) ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Optimize your marketing strategies through analytics and machine learning Key Features Understand how data science drives successful marketing campaigns Use machine learning for better customer engagement, retention, and product recommendations Extract insights from your data to optimize marketing strategies and increase profitability Book Description Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies. This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R. By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business. What you will learn Learn how to compute and visualize marketing KPIs in Python and R Master what drives successful marketing campaigns with data science Use machine learning to predict customer engagement and lifetime value Make product recommendations that customers are most likely to buy Learn how to use A/B testing for better marketing decision making Implement machine learning to understand different customer segments Who this book is for If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-adv...
    Note: Description based on online resource; title from title page (Safari, viewed May 1, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789346343/?ar
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    Online Resource
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  • 12
    Online Resource
    Online Resource
    Learning Python for forensics : leverage the power of Python in forensic investigations (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789342765 , 1789342767
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Computer networks ; Security measures ; Python (Computer program language) ; Computer crimes ; Investigation ; Data recovery (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Design, develop, and deploy innovative forensic solutions using Python Key Features Discover how to develop Python scripts for effective digital forensic analysis Master the skills of parsing complex data structures with Python libraries Solve forensic challenges through the development of practical Python scripts Book Description Digital forensics plays an integral role in solving complex cybercrimes and helping organizations make sense of cybersecurity incidents. This second edition of Learning Python for Forensics illustrates how Python can be used to support these digital investigations and permits the examiner to automate the parsing of forensic artifacts to spend more time examining actionable data. The second edition of Learning Python for Forensics will illustrate how to develop Python scripts using an iterative design. Further, it demonstrates how to leverage the various built-in and community-sourced forensics scripts and libraries available for Python today. This book will help strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. By the end of this book, you will build a collection of Python scripts capable of investigating an array of forensic artifacts and master the skills of extracting metadata and parsing complex data structures into actionable reports. Most importantly, you will have developed a foundation upon which to build as you continue to learn Python and enhance your efficacy as an investigator. What you will learn Learn how to develop Python scripts to solve complex forensic problems Build scripts using an iterative design Design code to accommodate present and future hurdles Leverage built-in and community-sourced libraries Understand the best practices in forensic programming Learn how to transform raw data into customized reports and visualizations Create forensic frameworks to automate analysis of multiple forensic artifacts Conduct effective and efficient investigations through programmatic processing Who this book is for If you are a forensics student, hobbyist, or professional seeking to increase your understanding in forensics through the use of a programming language, then Learning Python for Forensics is for you. You are not required to have previous experience in programming to learn and master the content within this book. This material, created by forensic professionals, was written with a unique perspective and understanding for ex...
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789341690/?ar
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  • 13
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    Getting started with Python for the Internet of Things : leverage the full potential of Python to prototype and build IoT projects using the Raspberry Pi (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781838553333 , 1838553339
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Internet of things ; Raspberry Pi (Computer) ; Machine-to-machine communications ; Electronic books ; Electronic books ; local
    Abstract: Build clever, collaborative, and powerful automation systems with the Raspberry Pi and Python. Key Features Create your own Pi-Rover or Pi-Hexipod robots Develop practical applications in Python using Raspberry Pi Build your own Jarvis, a highly advanced computerized AI Book Description This Learning Path takes you on a journey in the world of robotics and teaches you all that you can achieve with Raspberry Pi and Python. It teaches you to harness the power of Python with the Raspberry Pi 3 and the Raspberry Pi zero to build superlative automation systems that can transform your business. You will learn to create text classifiers, predict sentiment in words, and develop applications with the Tkinter library. Things will get more interesting when you build a human face detection and recognition system and a home automation system in Python, where different appliances are controlled using the Raspberry Pi. With such diverse robotics projects, you'll grasp the basics of robotics and its functions, and understand the integration of robotics with the IoT environment. By the end of this Learning Path, you will have covered everything from configuring a robotic controller, to creating a self-driven robotic vehicle using Python. Raspberry Pi 3 Cookbook for Python Programmers - Third Edition by Tim Cox, Dr. Steven Lawrence Fernandes Python Programming with Raspberry Pi by Sai Yamanoor, Srihari Yamanoor Python Robotics Projects by Prof. Diwakar Vaish What you will learn Build text classifiers and predict sentiment in words with the Tkinter library Develop human face detection and recognition systems Create a neural network module for optical character recognition Build a mobile robot using the Raspberry Pi as a controller Understand how to interface sensors, actuators, and LED displays work Apply machine learning techniques to your models Interface your robots with Bluetooth Who this book is for This Learning Path is specially designed for Python developers who want to take their skills to the next level by creating robots that can enhance people's lives. Familiarity with Python and electronics will aid understanding the concepts in this Learning Path.
    Note: Description based on online resource; title from title page (Safari, viewed April 5, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781838555795/?ar
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  • 14
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    Python network programming : conquer all your networking challenges with the powerful Python language (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788830232 , 1788830237
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Computer networks ; Management ; Client/server computing ; Electronic books ; Electronic books ; local
    Abstract: Power up your network applications with Python programming Key Features Master Python skills to develop powerful network applications Grasp the fundamentals and functionalities of SDN Design multi-threaded, event-driven architectures for echo and chat servers Book Description This Learning Path highlights major aspects of Python network programming such as writing simple networking clients, creating and deploying SDN and NFV systems, and extending your network with Mininet. You'll also learn how to automate legacy and the latest network devices. As you progress through the chapters, you'll use Python for DevOps and open source tools to test, secure, and analyze your network. Toward the end, you'll develop client-side applications, such as web API clients, email clients, SSH, and FTP, using socket programming. By the end of this Learning Path, you will have learned how to analyze a network's security vulnerabilities using advanced network packet capture and analysis techniques. This Learning Path includes content from the following Packt products: Practical Network Automation by Abhishek Ratan Mastering Python Networking by Eric Chou Python Network Programming Cookbook, Second Edition by Pradeeban Kathiravelu, Dr. M. O. Faruque Sarker What you will learn Create socket-based networks with asynchronous models Develop client apps for web APIs, including S3 Amazon and Twitter Talk to email and remote network servers with different protocols Integrate Python with Cisco, Juniper, and Arista eAPI for automation Use Telnet and SSH connections for remote system monitoring Interact with websites via XML-RPC, SOAP, and REST APIs Build networks with Ryu, OpenDaylight, Floodlight, ONOS, and POX Configure virtual networks in different deployment environments Who this book is for If you are a Python developer or a system administrator who wants to start network programming, this Learning Path gets you a step closer to your goal. IT professionals and DevOps engineers who are new to managing network devices or those with minimal experience looking to expand their knowledge and skills in Python will also find this Learning Path useful. Although prior knowledge of networking is not required, some experience in Python programming will be helpful for a better understanding of the concepts in the Learning Path.
    Note: Description based on online resource; title from title page (Safari, viewed March 19, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788835466/?ar
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  • 15
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    TensorFlow reinforcement learning quick start guide : get up and running with training and deploying intelligent, self-learning agents using Python (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789533446 , 1789533449
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: TensorFlow ; Reinforcement learning ; Neural networks (Computer science) ; Python (Computer program language) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Tensorflow to Create powerful software agents that can self-learn to perform real-world tasks Key Features Explore efficient Reinforcement Learning algorithms and code them using TensorFlow and Python Train Reinforcement Learning agents for problems, ranging from computer games to autonomous driving. Formulate and devise selective algorithms and techniques in your applications in no time. Book Description Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving. The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator. By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems. What you will learn Understand the theory and concepts behind modern Reinforcement Learning algorithms Code state-of-the-art Reinforcement Learning algorithms with discrete or continuous actions Develop Reinforcement Learning algorithms and apply them to training agents to play computer games Explore DQN, DDQN, and Dueling architectures to play Atari's Breakout using TensorFlow Use A3C to play CartPole and LunarLander Train an agent to drive a car autonomously in a simulator Who this book is for Data scientists and AI developers who wish to quickly get started with training effective reinforcement learning models in TensorFlow will find this book very useful. Prior knowledge of machine learning and deep learning concepts (...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 14, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789533583/?ar
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  • 16
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    Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789349702 , 1789349702
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications across computer vision and NLP Learn how a computer can navigate in complex environments with reinforcement learning Book Description With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you'll explore deep learning, and learn how to put machine learning to use in your projects. This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You'll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You'll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you'll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota. By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications. What you will learn Grasp the mathematical theory behind neural networks and deep learning processes Investigate and resolve computer vision challenges using convolutional networks and capsule networks Solve generative tasks using variational autoencoders and Generative Adversarial Networks Implement complex NLP tasks using recurrent networks (LSTM and GRU) and attention models Explore reinforcement learning and understand how agents behave in a complex environment Get up to date with applications of deep learning in autonomous vehicles Who this book is for This book is for data science practitioners, machine learning engineers, and those interested in deep learning who have a basic foundation in machine learning and some Python programming experience. A background in mathematics and conceptual understandi...
    Note: Description based on online resource; title from title page (Safari, viewed February 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789348460/?ar
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  • 17
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    Neural network projects with Python : the ultimate guide to using Python to explore the true power of neural networks through six projects (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789133318 , 1789133319
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Neural networks (Computer science) ; Machine learning ; Artificial intelligence ; Electronic books ; local ; Electronic books
    Abstract: Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key Features Discover neural network architectures (like CNN and LSTM) that are driving recent advancements in AI Build expert neural networks in Python using popular libraries such as Keras Includes projects such as object detection, face identification, sentiment analysis, and more Book Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learn Learn various neural network architectures and its advancements in AI Master deep learning in Python by building and training neural network Master neural networks for regression and classification Discover convolutional neural networks for image recognition Learn sentiment analysis on textual data using Long Short-Term Memory Build and train a highly accurate facial recognition security system Who this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.
    Note: Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: lizenzpflichtig
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  • 18
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    Foundations of Blockchain : the pathway to cryptocurrencies and decentralized blockchain applications (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789138191 , 1789138191
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Blockchains (Databases) ; Application software ; Development ; Cryptocurrencies ; Bitcoin ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn the foundations of blockchain technology - its core concepts and algorithmic solutions across cryptography, peer-to-peer technology, and game theory. Key Features Learn the core concepts and foundations of the blockchain and cryptocurrencies Understand the protocols and algorithms behind decentralized applications Master how to architect, build, and optimize blockchain applications Book Description Blockchain technology is a combination of three popular concepts: cryptography, peer-to-peer networking, and game theory. This book is for anyone who wants to dive into blockchain from first principles and learn how decentralized applications and cryptocurrencies really work. This book begins with an overview of blockchain technology, including key definitions, its purposes and characteristics, so you can assess the full potential of blockchain. All essential aspects of cryptography are then presented, as the backbone of blockchain. For readers who want to study the underlying algorithms of blockchain, you'll see Python implementations throughout. You'll then learn how blockchain architecture can create decentralized applications. You'll see how blockchain achieves decentralization through peer-to-peer networking, and how a simple blockchain can be built in a P2P network. You'll learn how these elements can implement a cryptocurrency such as Bitcoin, and the wider applications of blockchain work through smart contracts. Blockchain optimization techniques, and blockchain security strategies are then presented. To complete this foundation, we consider blockchain applications in the financial and non-financial sectors, and also analyze the future of blockchain. A study of blockchain use cases includes supply chains, payment systems, crowdfunding, and DAOs, which rounds out your foundation in blockchain technology. What you will learn The core concepts and technical foundations of blockchain The algorithmic principles and solutions that make up blockchain and cryptocurrencies Blockchain cryptography explained in detail How to realize blockchain projects with hands-on Python code How to architect the blockchain and blockchain applications Decentralized application development with MultiChain, NEO, and Ethereum Optimizing and enhancing blockchain performance and security Classical blockchain use cases and how to implement them Who this book is for This book is for anyone who wants to dive into blockchain technology from first principles and build a ...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 14, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789139396/?ar
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  • 19
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    Mastering Python scripting for system administrators : write scripts and automate them for real-world administration tasks using Python (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789134261 , 1789134269
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Information technology ; Management ; Electronic books ; Electronic books ; local
    Abstract: Leverage the features and libraries of Python to administrate your environment efficiently. Key Features Learn how to solve problems of system administrators and automate routine activities Learn to handle regular expressions, network administration Building GUI, web-scraping and database administration including data analytics Book Description Python has evolved over time and extended its features in relation to every possible IT operation. Python is simple to learn, yet has powerful libraries that can be used to build powerful Python scripts for solving real-world problems and automating administrators' routine activities. The objective of this book is to walk through a series of projects that will teach readers Python scripting with each project. This book will initially cover Python installation and quickly revise basic to advanced programming fundamentals. The book will then focus on the development process as a whole, from setup to planning to building different tools. It will include IT administrators' routine activities (text processing, regular expressions, file archiving, and encryption), network administration (socket programming, email handling, the remote controlling of devices using telnet/ssh, and protocols such as SNMP/DHCP), building graphical user interface, working with websites (Apache log file processing, SOAP and REST APIs communication, and web scraping), and database administration (MySQL and similar database data administration, data analytics, and reporting). By the end of this book, you will be able to use the latest features of Python and be able to build powerful tools that will solve challenging, real-world tasks What you will learn Understand how to install Python and debug Python scripts Understand and write scripts for automating testing and routine administrative activities Understand how to write scripts for text processing, encryption, decryption, and archiving Handle files, such as pdf, excel, csv, and txt files, and generate reports Write scripts for remote network administration, including handling emails Build interactive tools using a graphical user interface Handle Apache log files, SOAP and REST APIs communication Automate database administration and perform statistical analysis Who this book is for This book would be ideal for users with some basic understanding of Python programming and who are interested in scaling their programming skills to command line scripting and system administration. Prior ...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789133226/?ar
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  • 20
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    React Native cookbook : step-by-step recipes for solving common React Native development problems (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788990431 , 1788990439
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Application software ; Development ; Mobile apps ; Web site development ; JavaScript (Computer program language) ; Web sites ; Design ; Electronic books ; Electronic books ; local
    Abstract: Improve your React Native mobile development skills or transition from web development to mobile development with this practical solution-packed guide Key Features Learn strategies and techniques to face challenges in React Native mobile development head-on Leverage the best ways to use iOS and Android for React Native development while maximizing code reuse and cohesion Build engaging, performant user experiences with React Native Book Description If you are a developer looking to create mobile applications with maximized code reusability and minimized cost, then React Native is here to help. With this practical guide, you will be able to build attractive UIs, tackle common mobile development-related issues, and achieve improved performance in mobile environments. This book starts with common techniques for React Native customization and helps you set up your development platforms. Over the course of the book, a wide variety of step-by-step recipes are designed with both built-in React Native and custom third-party components that you will create, style, and animate. You will create real-world browser-based authentication, build a fully functional audio player, and integrate with Google maps. You will also explore different strategies for working with data, including leveraging the popular Redux library and optimizing your app's dataflow. You will then get an introduction to writing native device functionality for new and already existing native projects. Finally, you will learn how app deployment works, and tips and tricks for writing performant code. By the end of the book, you'll have gained enough knowledge to build full iOS and Android applications using React Native. What you will learn Build UI features and components using React Native Create advanced animations for UI components Develop universal apps that run on phones and tablets Leverage Redux to manage application flow and data Expose both custom native UI components and application logic to React Native Employ open-source third-party plugins to create React Native apps more efficiently Who this book is for If you're a JavaScript developer looking for a practical guide with step-by-step tutorials for developing feature rich mobile apps using React Native, then this book is for you. Though not required, some experience working with React will help you more easily understand the React Native concepts covered in this book. While React Native development can be done on a Windows mach...
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 22, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788991926/?ar
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  • 21
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    Spring 5.0 projects : build seven web development projects with Spring MVC, Angular 6, JHipster, WebFlux, and Spring Boot 2 (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788391979 , 1788391977
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spring (Software framework) ; Application software ; Development ; Web site development ; Web applications ; Electronic books ; Electronic books ; local
    Abstract: Discover the latest features of Spring framework by building robust, fast, and reactive web applications Key Features Take advantage of all the features of Spring 5.0 with third party tools to build a robust back end Secure Spring based web application using Spring Security framework with LDAP and OAuth protocol Develop robust and scalable microservice based applications on Spring Cloud, using Spring Boot Book Description Spring makes it easy to create RESTful applications, merge with social services, communicate with modern databases, secure your system, and make your code modular and easy to test. With the arrival of Spring Boot, developers can really focus on the code and deliver great value, with minimal contour. This book will show you how to build various projects in Spring 5.0, using its features and third party tools. We'll start by creating a web application using Spring MVC, Spring Data, the World Bank API for some statistics on different countries, and MySQL database. Moving ahead, you'll build a RESTful web services application using Spring WebFlux framework. You'll be then taken through creating a Spring Boot-based simple blog management system, which uses Elasticsearch as the data store. Then, you'll use Spring Security with the LDAP libraries for authenticating users and create a central authentication and authorization server using OAuth 2 protocol. Further, you'll understand how to create Spring Boot-based monolithic application using JHipster. Toward the end, we'll create an online book store with microservice architecture using Spring Cloud and Net?ix OSS components, and a task management system using Spring and Kotlin. By the end of the book, you'll be able to create coherent and ?exible real-time web applications using Spring Framework. What you will learn Build Spring based application using Bootstrap template and JQuery Understand the Spring WebFlux framework and how it uses Reactor library Interact with Elasticsearch for indexing, querying, and aggregating data Create a simple monolithic application using JHipster Use Spring Security and Spring Security LDAP and OAuth libraries for Authentication Develop a microservice-based application with Spring Cloud and Netflix Work on Spring Framework with Kotlin Who this book is for This book is for competent Spring developers who wish to understand how to develop complex yet flexible applications with Spring. You must have a good knowledge of Java programming and be familiar wit...
    Note: Description based on online resource; title from title page (Safari, viewed April 17, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788390415/?ar
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    Natural language processing fundamentals (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789955989 , 178995598X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Natural language processing (Computer science) ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. Key Features Assimilate key NLP concepts and terminologies Explore popular NLP tools and techniques Gain practical experience using NLP in application code Book Description If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language. What you will learn Obtain, verify, and clean data before transforming it into a correct format for use Perform data analysis and machine learning tasks using Python Understand the basics of computational linguistics Build models for general natural language processing tasks Evaluate the performance of a model with the right metrics Visualize, quantify, and perform exploratory analysis from any text data Who this book is for Natural Language Processing Fundamentals is designed for novice and mid-level data scientists and machine learning developers who want to gather and analyze text data to build an NLP-powered product. It'll help you to have prior experience of coding in Python using data types, writing functions, and importing libraries. Some experience with linguistics and probability is useful but not necessary.
    Note: Description based on online resource; title from cover (Safari, viewed May 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789954043/?ar
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    Getting started with Python : understand key data structures and use Python in object-oriented programming (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781838559984 , 1838559981
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Harness the power of Python objects and data structures to implement algorithms for analyzing your data and efficiently extracting information Key Features Turn your designs into working software by learning the Python syntax Write robust code with a solid understanding of Python data structures Understand when to use the functional or the OOP approach Book Description This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You'll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you've covered core topics, you'll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: Learn Python Programming - Second Edition by Fabrizio Romano Python Data Structures and Algorithms by Benjamin Baka Python 3 Object-Oriented Programming by Dusty Phillips What you will learn Use data structures and control flow to write code Use functions to bundle together a sequence of instructions Implement objects in Python by creating classes and defining methods Design public interfaces using abstraction, encapsulation and information hiding Raise, define, and manipulate exceptions using special error objects Create bulletproof and reliable software by writing unit tests Learn the common programming patterns and algorithms used in Python Who this book is for If you are relatively new to coding and want to write scripts or programs to accomplish tasks using Python, or if you are an object-oriented programmer for other languages and seeking a leg up in the world of Python, then this Learning Path is for you. Though not essential, it will help you to have basic knowledge of programming and OOP.
    Note: Description based on online resource; title from title page (Safari, viewed April 24, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781838551919/?ar
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    Advanced Python programming : build high performance, concurrent, and multi-threaded apps with Python using proven design patterns (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781838553692 , 183855369X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Create distributed applications with clever design patterns to solve complex problems Key Features Set up and run distributed algorithms on a cluster using Dask and PySpark Master skills to accurately implement concurrency in your code Gain practical experience of Python design patterns with real-world examples Book Description This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: ? Python High Performance - Second Edition by Gabriele Lanaro ? Mastering Concurrency in Python by Quan Nguyen ? Mastering Python Design Patterns by Sakis Kasampalis What you will learn Use NumPy and pandas to import and manipulate datasets Achieve native performance with Cython and Numba Write asynchronous code using asyncio and RxPy Design highly scalable programs with application scaffolding Explore abstract methods to maintain data consistency Clone objects using the prototype pattern Use the adapter pattern to make incompatible interfaces compatible Employ the strategy pattern to dynamically choose an algorithm Who this book is for This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed April 22, 2019)
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    Data wrangling with Python (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789804249 , 1789804248
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Data mining ; Electronic data processing ; Information visualization ; Electronic books ; local ; Electronic books
    Abstract: Simplify your ETL processes with these hands-on data hygiene tips, tricks, and best practices. Key Features Focus on the basics of data wrangling Study various ways to extract the most out of your data in less time Boost your learning curve with bonus topics like random data generation and data integrity checks Book Description For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain. The book starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The book will further help you grasp concepts through real-world examples and datasets. By the end of this book, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently. What you will learn Use and manipulate complex and simple data structures Harness the full potential of DataFrames and numpy.array at run time Perform web scraping with BeautifulSoup4 and html5lib Execute advanced string search and manipulation with RegEX Handle outliers and perform data imputation with Pandas Use descriptive statistics and plotting techniques Practice data wrangling and modeling using data generation techniques Who this book is for Data Wrangling with Python is designed for developers, data analysts, and business analysts who are keen to pursue a career as a full-fledged data scientist or analytics expert. Although, this book is for beginners, prior working knowledge of Python is necessary to easily grasp the concepts covered here. It will also help to have rudimentary knowledge of relational database and SQL.
    Note: Description based on online resource; title from title page (Safari, viewed April 18, 2019)
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    Hands-on machine learning with IBM Watson : leverage IBM Watson to implement machine learning techniques and algorithms using Python (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789616279 , 1789616271
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Python (Computer program language) ; Watson (Computer) ; Computer algorithms ; Electronic books ; Electronic books ; local
    Abstract: Learn how to build complete machine learning systems with IBM Cloud and Watson Machine learning services Key Features Implement data science and machine learning techniques to draw insights from real-world data Understand what IBM Cloud platform can help you to implement cognitive insights within applications Understand the role of data representation and feature extraction in any machine learning system Book Description IBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio. You will also be guided through deep learning and neural network principles on the IBM Cloud using TensorFlow. With the help of NLP techniques, you can then brush up on building a chatbot. In later chapters, you will cover three powerful case studies, including the facial expression classification platform, the automated classification of lithofacies, and the multi-biometric identity authentication platform, helping you to become well versed with these methodologies. By the end of this book, you will be ready to build efficient machine learning solutions on the IBM Cloud and draw insights from the data at hand using real-world examples. What you will learn Understand key characteristics of IBM machine learning services Run supervised and unsupervised techniques in the cloud Understand how to create a Spark pipeline in Watson Studio Implement deep learning and neural networks on the IBM Cloud with TensorFlow Create a complete, cloud-based facial expression classification solution Use biometric traits to build a cloud-based human identification system Who this book is for This beginner-level book is for data scientists and machine learning engineers who want to get started with IBM Cloud and its machine learning services using practical examples. Basic knowledge of Python and some understanding of machine learning will be useful.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789611854/?ar
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    Intelligent projects using Python : 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788994866 , 1788994868
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Artificial intelligence ; Machine learning ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key Features A go-to guide to help you master AI algorithms and concepts 8 real-world projects tackling different challenges in healthcare, e-commerce, and surveillance Use TensorFlow, Keras, and other Python libraries to implement smart AI applications Book Description This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. You will assimilate various neural network architectures such as CNN, RNN, LSTM, to solve critical new world challenges. You will learn to train a model to detect diabetic retinopathy conditions in the human eye and create an intelligent system for performing a video-to-text translation. You will use the transfer learning technique in the healthcare domain and implement style transfer using GANs. Later you will learn to build AI-based recommendation systems, a mobile app for sentiment analysis and a powerful chatbot for carrying customer services. You will implement AI techniques in the cybersecurity domain to generate Captchas. Later you will train and build autonomous vehicles to self-drive using reinforcement learning. You will be using libraries from the Python ecosystem such as TensorFlow, Keras and more to bring the core aspects of machine learning, deep learning, and AI. By the end of this book, you will be skilled to build your own smart models for tackling any kind of AI problems without any hassle. What you will learn Build an intelligent machine translation system using seq-2-seq neural translation machines Create AI applications using GAN and deploy smart mobile apps using TensorFlow Translate videos into text using CNN and RNN Implement smart AI Chatbots, and integrate and extend them in several domains Create smart reinforcement, learning-based applications using Q-Learning Break and generate CAPTCHA using Deep Learning and Adversarial Learning Who this book is for This book is intended for data scientists, machine learning professionals, and deep learning practitioners who are ready to extend their knowledge and potential in AI. If you want to build real-life smart systems to play a crucial role in every complex domain, then this book is w...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788996921/?ar
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    Hands-on big data analytics with PySpark : analyze large datasets and discover techniques for testing, immunizing, and parallelizing Spark jobs (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781838648831 , 1838648836
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: SPARK (Computer program language) ; Application software ; Development ; Big data ; Electronic data processing ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobs Key Features Work with large amounts of agile data using distributed datasets and in-memory caching Source data from all popular data hosting platforms, such as HDFS, Hive, JSON, and S3 Employ the easy-to-use PySpark API to deploy big data Analytics for production Book Description Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs. You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark. By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively. What you will learn Get practical big data experience while working on messy datasets Analyze patterns with Spark SQL to improve your business intelligence Use PySpark's interactive shell to speed up development time Create highly concurrent Spark programs by leveraging immutability Discover ways to avoid the most expensive operation in the Spark API: the shuffle operation Re-design your jobs to use reduceByKey instead of groupBy Create robust processing pipelines by testing Apache Spark jobs Who this book is for This book is for developers, data scientists, business analysts, or anyone who needs to reliably analyze large amounts of large-scale, real-world data. Whether you're tasked with creating your company's business intelligence function or creating great data platforms for your machine learning models, or are looking to use code to mag...
    Note: Description based on online resource; title from title page (Safari, viewed May 9, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781838644130/?ar
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    Ensemble machine learning cookbook : over 35 practical recipes to explore ensemble machine learning techniques using Python (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789132502 , 1789132509
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features Apply popular machine learning algorithms using a recipe-based approach Implement boosting, bagging, and stacking ensemble methods to improve machine learning models Discover real-world ensemble applications and encounter complex challenges in Kaggle competitions Book Description Ensemble modeling is an approach used to improve the performance of machine learning models. It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking. The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis. You'll then learn to implement tasks related to statistical and machine learning algorithms to understand the ensemble of multiple heterogeneous algorithms. It will also ensure that you don't miss out on key topics, such as like resampling methods. As you progress, you'll get a better understanding of bagging, boosting, stacking, and working with the Random Forest algorithm using real-world examples. The book will highlight how these ensemble methods use multiple models to improve machine learning results, as compared to a single model. In the concluding chapters, you'll delve into advanced ensemble models using neural networks, natural language processing, and more. You'll also be able to implement models such as fraud detection, text categorization, and sentiment analysis. By the end of this book, you'll be able to harness ensemble techniques and the working mechanisms of machine learning algorithms to build intelligent models using individual recipes. What you will learn Understand how to use machine learning algorithms for regression and classification problems Implement ensemble techniques such as averaging, weighted averaging, and max-voting Get to grips with advanced ensemble methods, such as bootstrapping, bagging, and stacking Use Random Forest for tasks such as classification and regression Implement an ensemble of homogeneous and heterogeneous machine learning algorithms Learn and implement various boosting techniques, such as AdaBoost, Gradient Boosting Machine, and XGBoost Who this book is for This book is designed fo...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789136609/?ar
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    Python machine learning blueprints : put your machine learning concepts to the test by developing real-world smart projects (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788997775 , 1788997778
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Key Features Get to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and Keras Implement advanced concepts and popular machine learning algorithms in real-world projects Build analytics, computer vision, and neural network projects Book Description Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you'll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you'll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you'll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you'll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you'll be able to analyze data seamlessly and make a powerful impact through your projects. What you will learn Understand the Python data science stack and commonly used algorithms Build a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window Understand NLP concepts by creating a custom news feed Create applications that will recommend GitHub repositories based on ones you've starred, watched, or forked Gain the skills to build a chatbot from scratch using PySpark Develop a market-prediction app using stock data Delve into advanced concepts such as computer vision, neural networks, and deep learning Who this book is for This book is for machine learning practitioners, data scientists, and...
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788994170/?ar
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    Hands-on penetration testing with Python : enhance your ethical hacking skills to build automated and intelligent systems (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788999465 , 1788999460
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Penetration testing (Computer security) ; Electronic books ; Electronic books ; local
    Abstract: Implement defensive techniques in your ecosystem successfully with Python Key Features Identify and expose vulnerabilities in your infrastructure with Python Learn custom exploit development . Make robust and powerful cybersecurity tools with Python Book Description With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers. Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you'll explore the advanced uses of Python in the domain of penetration testing and optimization. You'll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you'll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python. By the end of this book, you'll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits. What you will learn Get to grips with Custom vulnerability scanner development Familiarize yourself with web application scanning automation and exploit development Walk through day-to-day cybersecurity scenarios that can be automated with Python Discover enterprise-or organization-specific use cases and threat-hunting automation Understand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows. Understand web scraping in Python and use it for processing web responses Explore Security Operations Centre (SOC) use cases Get to understand Data Science, Python, and cybersecurity all under one hood Who this book is for If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecu...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788990820/?ar
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    Hands-on Blockchain for Python developers : gain blockchain programming skills to build decentralized applications using Python (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788624640 , 1788624645
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Blockchains (Databases) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Implement real-world decentralized applications using Python, Vyper, Populus, and Ethereum Key Features Stay up-to-date with everything you need to know about the blockchain ecosystem Implement smart contracts, wallets, and decentralized applications(DApps) using Python libraries Get deeper insights into storing content in a distributed storage platform Book Description Blockchain is seen as the main technological solution that works as a public ledger for all cryptocurrency transactions. This book serves as a practical guide to developing a full-fledged decentralized application with Python to interact with the various building blocks of blockchain applications. Hands-On Blockchain for Python Developers starts by demonstrating how blockchain technology and cryptocurrency hashing works. You will understand the fundamentals and benefits of smart contracts such as censorship resistance and transaction accuracy. As you steadily progress, you'll go on to build smart contracts using Vyper, which has a similar syntax to Python. This experience will further help you unravel the other benefits of smart contracts, including reliable storage and backup, and efficiency. You'll also use web3.py to interact with smart contracts and leverage the power of both the web3.py and Populus framework to build decentralized applications that offer security and seamless integration with cryptocurrencies. As you explore later chapters, you'll learn how to create your own token on top of Ethereum and build a cryptocurrency wallet graphical user interface (GUI) that can handle Ethereum and Ethereum Request for Comments (ERC-20) tokens using the PySide2 library. This will enable users to seamlessly store, send, and receive digital money. Toward the end, you'll implement InterPlanetary File System (IPFS) technology in your decentralized application to provide a peer-to-peer filesystem that can store and expose media. By the end of this book, you'll be well-versed in blockchain programming and be able to build end-to-end decentralized applications on a range of domains using Python. What you will learn Understand blockchain technology and what makes it an immutable database Use the features of web3.py API to interact with the smart contract Create your own cryptocurrency and token in Ethereum using Vyper Use IPFS features to store content on the decentralized storage platform Implement a Twitter-like decentralized application with a desktop frontend Build decentralized app...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 28, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788627856/?ar
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    Data science for marketing analytics (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789952100 , 1789952107
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Marketing ; Data processing ; Marketing research ; Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key Features Study new techniques for marketing analytics Explore uses of machine learning to power your marketing analyses Work through each stage of data analytics with the help of multiple examples and exercises Book Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learn Analyze and visualize data in Python using pandas and Matplotlib Study clustering techniques, such as hierarchical and k-means clustering Create customer segments based on manipulated data Predict customer lifetime value using linear regression Use classification algorithms to understand customer choice Optimize classification algorithms to extract maximal information Who this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.
    Note: Includes bibliographical references. - Description based on online resource; title from copyright page (Safari, viewed May 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789959413/?ar
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    Learn web development with Python : get hands-on with Python programming and Django web development (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789950885 , 1789950880
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Application software ; Development ; Web site development ; Electronic books ; Electronic books ; local
    Abstract: A comprehensive guide to Python programming for web development using the most popular Python web framework - Django Key Features Learn the fundamentals of programming with Python and building web apps Build web applications from scratch with Django Create real-world RESTful web services with the latest Django framework Book Description If you want to develop complete Python web apps with Django, this Learning Path is for you. It will walk you through Python programming techniques and guide you in implementing them when creating 4 professional Django projects, teaching you how to solve common problems and develop RESTful web services with Django and Python. You will learn how to build a blog application, a social image bookmarking website, an online shop, and an e-learning platform. Learn Web Development with Python will get you started with Python programming techniques, show you how to enhance your applications with AJAX, create RESTful APIs, and set up a production environment for your Django projects. Last but not least, you'll learn the best practices for creating real-world applications. By the end of this Learning Path, you will have a full understanding of how Django works and how to use it to build web applications from scratch. This Learning Path includes content from the following Packt products: ? Learn Python Programming by Fabrizio Romano ? Django RESTful Web Services by Gaston C. Hillar ? Django Design Patterns and Best Practices by Arun Ravindran What you will learn Explore the fundamentals of Python programming with interactive projects Grasp essential coding concepts along with the basics of data structures and control flow Develop RESTful APIs from scratch with Django and the Django REST Framework Create automated tests for RESTful web services Debug, test, and profile RESTful web services with Django and the Django REST Framework Use Django with other technologies such as Redis and Celery Who this book is for If you have little experience in coding or Python and want to learn how to build full-fledged web apps, this Learning Path is for you. No prior experience with RESTful web services, Python, or Django is required, but basic Python programming experience is needed to understand the concepts covered.
    Note: Description based on online resource; title from title page (Safari, viewed February 18, 2019)
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    Python Interviews : discussions with Python experts (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788391764 , 1788391764
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Expert insight
    Parallel Title: Erscheint auch als
    Keywords: Python (Computer program language) ; Computer programming
    Note: Description based on online resource; title from title page (viewed April 2, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
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    Numerical computing with Python : harness the power of Python to analyze and find hidden patterns in the data (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789957228 , 1789957222
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Data mining ; Information visualization ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Understand, explore, and effectively present data using the powerful data visualization techniques of Python Key Features Use the power of Pandas and Matplotlib to easily solve data mining issues Understand the basics of statistics to build powerful predictive data models Grasp data mining concepts with helpful use-cases and examples Book Description Data mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining. You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models. By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional. This Learning Path includes content from the following Packt products: Statistics for Machine Learning by Pratap Dangeti Matplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin Yim Pandas Cookbook by Theodore Petrou What you will learn Understand the statistical fundamentals to build data models Split data into independent groups Apply aggregations and transformations to each group Create impressive data visualizations Prepare your data and design models Clean up data to ease data analysis and visualization Create insightful visualizations with Matplotlib and Seaborn Customize the model to suit your own predictive goals Who this book is for If you want to learn how to use the many libraries of Python to extract impactful information from your data and present it as engaging visuals, then this is the ideal Learning Path for you. Some basic knowledge of Python is enough to get started with this Learning Path.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 20, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789953633/?ar
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    Applied data science with Python and Jupyter (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789951929 , 1789951925
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Information visualization ; Electronic data processing ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications. Key Features Get up and running with the Jupyter ecosystem and some example datasets Learn about key machine learning concepts such as SVM, KNN classifiers, and Random Forests Discover how you can use web scraping to gather and parse your own bespoke datasets Book Description Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations. What you will learn Get up and running with the Jupyter ecosystem Identify potential areas of investigation and perform exploratory data analysis Plan a machine learning classification strategy and train classification models Use validation curves and dimensionality reduction to tune and enhance your models Scrape tabular data from web pages and transform it into Pandas DataFrames Create interactive, web-friendly visualizations to clearly communicate your findings Who this book is for Applied Data Science with Python and Jupyter is ideal for professionals with a variety of job descriptions across a large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries such as Pandas, Matplotlib, and Pandas providing you a useful head start.
    Note: Description based on online resource; title from copyright page (Safari, viewed June 12, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789958171/?ar
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    Practical network automation : a beginner's guide to automating and optimizing networks using Python, Ansible, and more (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789950403 , 1789950406
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Computer networks ; Management ; Python (Computer program language) ; Electronic data processing ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Python, Ansible and other network automation tools to make your network robust and more secure Key Features Get introduced to the concept of network automation with relevant use cases Apply Continuous Integration and DevOps to improve your network performance Implement effective automation using tools such as Python, Ansible, and more Book Description Network automation is the use of IT controls to supervise and carry out everyday network management functions. It plays a key role in network virtualization technologies and network functions. The book starts by providing an introduction to network automation, and its applications, which include integrating DevOps tools to automate the network efficiently. It then guides you through different network automation tasks and covers various data digging and performing tasks such as ensuring golden state configurations using templates, interface parsing. This book also focuses on Intelligent Operations using Artificial Intelligence and troubleshooting using chatbots and voice commands. The book then moves on to the use of Python and the management of SSH keys for machine-to-machine (M2M) communication, all followed by practical use cases. The book also covers the importance of Ansible for network automation, including best practices in automation; ways to test automated networks using tools such as Puppet, SaltStack, and Chef; and other important techniques. Through practical use-cases and examples, this book will acquaint you with the various aspects of network automation. It will give you the solid foundation you need to automate your own network without any hassle. What you will learn Get started with the fundamental concepts of network automation Perform intelligent data mining and remediation based on triggers Understand how AIOps works in operations Trigger automation through data factors Improve your data center's robustness and security through data digging Get access infrastructure through API Framework for chatbot and voice interactive troubleshootings Set up communication with SSH-based devices using Netmiko Who this book is for If you are a network engineer or a DevOps professional looking for an extensive guide to help you automate and manage your network efficiently, then this book is for you. No prior experience with network automation is required to get started, however you will need some exposure to Python programming to get the most out of this book.
    Note: Previous edition published: 2017. - Description based on online resource; title from title page (Safari, viewed February 26, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789955651/?ar
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    Applied deep learning with Python : use scikit-learn, TensorFlow, and Keras to create intelligent systems and machine learning solutions (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789806991 , 1789806992
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: A hands-on guide to deep learning that's filled with intuitive explanations and engaging practical examples Key Features Designed to iteratively develop the skills of Python users who don't have a data science background Covers the key foundational concepts you'll need to know when building deep learning systems Full of step-by-step exercises and activities to help build the skills that you need for the real-world Book Description Taking an approach that uses the latest developments in the Python ecosystem, you'll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. We'll explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. It's okay if these terms seem overwhelming; we'll show you how to put them to work. We'll build upon our classification coverage by taking a quick look at ethical web scraping and interactive visualizations to help you professionally gather and present your analysis. It's after this that we start building out our keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data. By guiding you through a trained neural network, we'll explore common deep learning network architectures (convolutional, recurrent, generative adversarial) and branch out into deep reinforcement learning before we dive into model optimization and evaluation. We'll do all of this whilst working on a production-ready web application that combines Tensorflow and Keras to produce a meaningful user-friendly result, leaving you with all the skills you need to tackle and develop your own real-world deep learning projects confidently and effectively. What you will learn Discover how you can assemble and clean your very own datasets Develop a tailored machine learning classification strategy Build, train and enhance your own models to solve unique problems Work with production-ready frameworks like Tensorflow and Keras Explain how neural networks operate in clear and simple terms Understand how to deploy your predictions to the web Who this book is for If you're a Python programmer stepping into the world of data science, this is the ideal way to get started.
    Note: Description based on online resource; title from title page (Safari, viewed December 3, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789804744/?ar
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    Hands-on image processing with Python : expert techniques for advanced image analysis and effective interpretation of image data (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789341850 , 178934185X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Image processing ; Python (Computer program language) ; Computer vision ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Explore the mathematical computations and algorithms for image processing using popular Python tools and frameworks. Key Features Practical coverage of every image processing task with popular Python libraries Includes topics such as pseudo-coloring, noise smoothing, computing image descriptors Covers popular machine learning and deep learning techniques for complex image processing tasks Book Description Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python. The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, we will have learned to implement various algorithms for efficient image processing. What you will learn Perform basic data pre-processing tasks such as image denoising and spatial filtering in Python Implement Fast Fourier Transform (FFT) and Frequency domain filters (e.g., Weiner) in Python Do morphological image processing and segment images with different algorithms Learn techniques to extract features from images and match images Write Python code to implement supervised / unsupervised machine learning algorithms for image processing Use deep learning models for image classification, segmentation, object detection and style transfer Who this book is for This book is for Computer Vision Engineers, and machine learning developers who are good with Python programming and want to explore details and complexities of image processing. No pri...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 1, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789343731/?ar
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    Magento 2 development quick start guide : build better stores by extending Magento (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789345469 , 1789345464
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Magento (Web site development tool) ; Web site development ; Electronic commerce ; Web sites ; Design ; Electronic books ; Electronic books ; local
    Abstract: Create an interactive online store and customize it further using Magento Key Features Straightforward guide to developing with Magento Examples of different types of extension Customize the Magento storefront and admin areas Book Description Magento is an open source, enterprise-level e-commerce platform with unlimited scope for customization. This makes it a great choice not only for vendors, but for developers as well. This book guides you through Magento development, teaching you how to develop modules that extend or change its functionality, leading to more flexible and proftable Magento stores. You start with a structural overview of the key Magento development components. You will learn where things such as plugins, events, models, controllers, layouts, and UI components ft into the development landscape. You will go through examples of using these components to extend Magento. As you progress, you will be building a diverse series of small but practical Magento modules. By the end of this book, you will not only have a solid foundation in the Magento development architecture; you will also have practical experience of developing modules to customize and extend Magento stores. What you will learn Develop a simple shipping module Build admin interfaces with the built-in form and listing UI components Implement JavaScript components for improved customer experience Accommodate vendor needs by adding new catalog-related features Develop your way to a better checkout Improve customer interaction with new customer-related extensions Create new web APIs to make your modules more extensible Who this book is for This book is for competent PHP developers, with only basic knowledge of the Magento platform required.
    Note: Description based on online resource; title from title page (Safari, viewed October 25, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789343441/?ar
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    Python data science essentials : a practitioner's guide covering essential data science principles, tools, and techniques (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789531893 , 1789531896
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Python (Computer program language) ; Database management ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Gain useful insights from your data using popular data science tools Key Features A one-stop guide to Python libraries such as pandas and NumPy Comprehensive coverage of data science operations such as data cleaning and data manipulation Choose scalable learning algorithms for your data science tasks Book Description Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn. The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You'll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost. By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users What you will learn Set up your data science toolbox on Windows, Mac, and Linux Use the core machine learning methods offered by the scikit-learn library Manipulate, fix, and explore data to solve data science problems Learn advanced explorative and manipulative techniques to solve data operations Optimize your machine learning models for optimized performance Explore and cluster graphs, taking advantage of interconnections and links in your data Who this book is for If you're a data science entrant, data analyst, or data engineer, this book will help you get ready to tackle real-world data science problems without wasting any time. Basic knowledge of probability/statistics and Python coding experience will assist you in understanding the concepts covered in this book. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support an...
    Note: Description based on online resource; title from title page (viewed November 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789537864/?ar
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    Hands-on data structures and algorithms with Python : write complex and powerful using the latest features of Python 3.7 (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788991933 , 1788991931
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Data structures (Computer science) ; Computer algorithms ; Electronic books ; Electronic books ; local
    Abstract: Learn to implement complex data structures and algorithms using Python Key Features Understand the analysis and design of fundamental Python data structures Explore advanced Python concepts such as Big O notation and dynamic programming Learn functional and reactive implementations of traditional data structures Book Description Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms. What you will learn Understand object representation, attribute binding, and data encapsulation Gain a solid understanding of Python data structures using algorithms Study algorithms using examples with pictorial representation Learn complex algorithms through easy explanation, implementing Python Build sophisticated and efficient data applications in Python Understand common programming algorithms used in Python data science Write efficient and robust code in Python 3.7 Who this book is for This book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.
    Note: Description based on online resource; title from title page (viewed February 6, 2019)
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    Artificial intelligence by example : develop machine intelligence from scratch using real artificial intelligence use cases (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788990028 , 1788990021
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Data processing ; Application software ; Development ; Python (Computer program language) ; Cloud computing ; Electronic books ; Electronic books ; local
    Abstract: Be an adaptive thinker that leads the way to Artificial Intelligence About This Book AI-based examples to guide you in designing and implementing machine intelligence Develop your own method for future AI solutions Acquire advanced AI, machine learning, and deep learning design skills Who This Book Is For Artificial Intelligence by Example is a simple, explanatory, and descriptive guide for junior developers, experienced developers, technology consultants, and those interested in AI who want to understand the fundamentals of Artificial Intelligence and implement it practically by devising smart solutions. Prior experience with Python and statistical knowledge is essential to make the most out of this book. What You Will Learn Use adaptive thinking to solve real-life AI case studies Rise beyond being a modern-day factory code worker Acquire advanced AI, machine learning, and deep learning designing skills Learn about cognitive NLP chatbots, quantum computing, and IoT and blockchain technology Understand future AI solutions and adapt quickly to them Develop out-of-the-box thinking to face any challenge the market presents In Detail Artificial Intelligence has the potential to replicate humans in every field. This book serves as a starting point for you to understand how AI is built, with the help of intriguing examples and case studies. Artificial Intelligence By Example will make you an adaptive thinker and help you apply concepts to real-life scenarios. Using some of the most interesting AI examples, right from a simple chess engine to a cognitive chatbot, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks. You will move on to designing AI solutions in a simple manner rather than get confused by complex architectures and techniques. This comprehensive guide will be a starter kit for you to develop AI applications on your own. By the end of this book, will have understood the fundamentals of AI and worked through a number of case studies that will help you develop business vision. Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of Artificial Intelligence Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your a...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed June 27, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788990547/?ar
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    Hands-on machine learning for algorithmic trading : design and implement investment strategies based on smart algorithms that learn from data using Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789342710 , 1789342716
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Python (Computer program language) ; Finance ; Data processing ; Finance ; Statistical methods ; Electronic books ; Electronic books ; local
    Abstract: Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features Implement machine learning algorithms to build, train, and validate algorithmic models Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn Implement machine learning techniques to solve investment and trading problems Leverage market, fundamental, and alternative data to research alpha factors Design and fine-tune supervised, unsupervised, and reinforcement learning models Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn Integrate machine learning models into a live trading strategy on Quantopian Evaluate strategies using reliable backtesting methodologies for time series Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Ma...
    Note: Description based on online resource; title from title page (Safari, viewed February 25, 2019)
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    Bioinformatics with Python cookbook : learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789349986 , 1789349982
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Bioinformatics ; Python (Computer program language) ; Computational biology ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Discover modern, next-generation sequencing libraries from Python ecosystem to analyze large amounts of biological data Key Features Perform complex bioinformatics analysis using the most important Python libraries and applications Implement next-generation sequencing, metagenomics, automating analysis, population genetics, and more Explore various statistical and machine learning techniques for bioinformatics data analysis Book Description Bioinformatics is an active research field that uses a range of simple-to-advanced computations to extract valuable information from biological data. This book covers next-generation sequencing, genomics, metagenomics, population genetics, phylogenetics, and proteomics. You'll learn modern programming techniques to analyze large amounts of biological data. With the help of real-world examples, you'll convert, analyze, and visualize datasets using various Python tools and libraries. This book will help you get a better understanding of working with a Galaxy server, which is the most widely used bioinformatics web-based pipeline system. This updated edition also includes advanced next-generation sequencing filtering techniques. You'll also explore topics such as SNP discovery using statistical approaches under high-performance computing frameworks such as Dask and Spark. By the end of this book, you'll be able to use and implement modern programming techniques and frameworks to deal with the ever-increasing deluge of bioinformatics data. What you will learn Learn how to process large next-generation sequencing (NGS) datasets Work with genomic dataset using the FASTQ, BAM, and VCF formats Learn to perform sequence comparison and phylogenetic reconstruction Perform complex analysis with protemics data Use Python to interact with Galaxy servers Use High-performance computing techniques with Dask and Spark Visualize protein dataset interactions using Cytoscape Use PCA and Decision Trees, two machine learning techniques, with biological datasets Who this book is for This book is for Data data Scientistsscientists, Bioinformatics bioinformatics analysts, researchers, and Python developers who want to address intermediate-to-advanced biological and bioinformatics problems using a recipe-based approach. Working knowledge of the Python programming language is expected.
    Note: Previous edition published: 2015. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 1, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789344691/?ar
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    Matplotlib for Python developers : effective techniques for data visualization with Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788628136 , 1788628136
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Matplotlib to visualize and understand your data more effectively About This Book Perform effective data visualization with Matplotlib and get actionable insights from your data Design attractive graphs, charts, and 2D plots, and deploy them to the web Get the most out of Matplotlib in this practical guide with updated code and examples Who This Book Is For This book is essentially for anyone who wants to create intuitive data visualizations using the Matplotlib library. If you're a data scientist or analyst and wish to create attractive visualizations using Python, you'll find this book useful. Some knowledge of Python programming is all you need to get started. What You Will Learn Create 2D and 3D static plots such as bar charts, heat maps, and scatter plots Get acquainted with GTK+3, Qt5, and wxWidgets to understand the UI backend of Matplotlib Develop advanced static plots with third-party packages such as Pandas, GeoPandas, and Seaborn Create interactive plots with real-time updates Develop web-based, Matplotlib-powered graph visualizations with third-party packages such as Django Write data visualization code that is readily expandable on the cloud platform In Detail Python is a general-purpose programming language increasingly being used for data analysis and visualization. Matplotlib is a popular data visualization package in Python used to design effective plots and graphs. This is a practical, hands-on resource to help you visualize data with Python using the Matplotlib library. Matplotlib for Python Developers, Second Edition shows you how to create attractive graphs, charts, and plots using Matplotlib. You will also get a quick introduction to third-party packages, Seaborn, Pandas, Basemap, and Geopandas, and learn how to use them with Matplotlib. After that, you'll embed and customize your plots in third-party tools such as GTK+3, Qt 5, and wxWidgets. You'll also be able to tweak the look and feel of your visualization with the help of practical examples provided in this book. Further on, you'll explore Matplotlib 2.1.x on the web, from a cloud-based platform using third-party packages such as Django. Finally, you will integrate interactive, real-time visualization techniques into your current workflow with the help of practical real-world examples. By the end of this book, you'll be thoroughly comfortable with using the popular Python data visualization library Matplotlib 2.1.x and leveraging its power to bu...
    Note: Previous edition published: 2009. - Description based on online resource; title from title page (Safari, viewed May 22, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788625173/?ar
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    OpenCV 3.x with Python by example : make the most of OpenCV and Python to build applications for object recognition and augmented reality (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788396769 , 1788396766
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; OpenCV (Computer program language) ; Computer vision ; Application software ; Development ; Cloud computing ; Electronic books ; Electronic books ; local
    Abstract: Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV. About This Book Learn how to apply complex visual effects to images with OpenCV 3.x and Python Extract features from an image and use them to develop advanced applications Build algorithms to help you understand image content and perform visual searches Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented reality Who This Book Is For This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on. What You Will Learn Detect shapes and edges from images and videos How to apply filters on images and videos Use different techniques to manipulate and improve images Extract and manipulate particular parts of images and videos Track objects or colors from videos Recognize specific object or faces from images and videos How to create Augmented Reality applications Apply artificial neural networks and machine learning to improve object recognition In Detail Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease. We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular Ope...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed February 21, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788396905/?ar
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    Learning Node.js development : learn the fundamentals of Node.js, and deploy and test Node.js applications on the web (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788396349 , 1788396340
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Web applications ; Development ; Web site development ; Electronic books ; Electronic books ; local
    Abstract: A comprehensive, easy-to-follow guide to creating complete Node apps and understanding how to build, deploy, and test your own apps. About This Book Entirely project-based and practical Explains the "Why" of Node.js features, not just the "how", providing you with a deep understanding and enabling you to easily apply concepts in your own applications Covers the full range of technologies around Node.js - NPM, version control with Git, and much more Who This Book Is For This book targets anyone looking to launch their own Node applications, switch careers, or freelance as a Node developer. You should have a basic understanding of JavaScript in order to follow this course. What You Will Learn Learn the fundamentals of Node Build apps that respond to user input Master working with servers Learn how to test and debug applications Deploy and update your apps in the real world Create responsive asynchronous web applications In Detail Learning Node.js Development is a practical, project-based book that provides you with all you need to get started as a Node.js developer. Node is a ubiquitous technology on the modern web, and an essential part of any web developers' toolkit. If you are looking to create real-world Node applications, or you want to switch careers or launch a side project to generate some extra income, then you're in the right place. This book has been written around a single goal-turning you into a professional Node developer capable of developing, testing, and deploying real-world production applications. Learning Node.js Development is built from the ground up around the latest version of Node.js (version 9.x.x). You'll be learning all the cutting-edge features available only in the latest software versions. This book cuts through the mass of information available around Node and delivers the essential skills that you need to become a Node developer. It takes you through creating complete apps and understanding how to build, deploy, and test your own Node apps. It maps out everything in a comprehensive, easy-to-follow package designed to get you up and running quickly. Style and approach This book is entirely project-based. From the very beginning you'll be programming every single app and completing various challenges designed to help test and reinforce what you've learned. There's no copying-and-pasting here. This book is about writing code and building projects. Downloading the example code for this book You can download the examp...
    Note: Description based on online resource; title from title page (Safari, viewed February 27, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788395540/?ar
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    Function Python programming : discover the power of functional programming, generator functions, lazy evaluation, the built-in itertools library, and monads (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788621854 , 1788621859
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Create succinct and expressive implementations with functional programming in Python About This Book Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance Get familiar with complex concepts such as monads, concurrency, and immutability Apply functional Python to common Exploratory Data Analysis (EDA) programming problems Who This Book Is For This book is for Python developers who would like to perform Functional programming with Python. Python Programming knowledge is assumed. What You Will Learn Use Python's generator functions and generator expressions to work with collections in a non-strict (or lazy) manner Utilize Python library modules including itertools, functools, multiprocessing, and concurrent features to ensure efficient functional programs Use Python strings with object-oriented suffix notation and prefix notation Avoid stateful classes with families of tuples Design and implement decorators to create composite functions Use functions such as max(), min(), map(), filter(), and sorted() Write higher-order functions In Detail If you're a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you'll explore common functional features such as first-class and higher-order functions, pure functions, and more. You'll see how these are accomplished in Python 3.6 to give you the core foundations you'll build upon. After that, you'll discover common functional optimizations for Python to help your apps reach even higher speeds. You'll learn FP concepts such as lazy evaluation using Python's generator functions and expressions. Moving forward, you'll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you'll at look at the PyMonad project and some larger examples to put everything into perspective. Style and approach This book provides a general overview of functional concepts and then delves deeper into the functional features, showing you how the Python standard library fits the functional programming model. It also dem...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed May 16, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788627061/?ar
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    Secret recipes of the Python ninja : over 70 recipes that uncover powerful programming tactics in Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788290845 , 1788290844
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Test your Python programming skills by solving real-world problems About This Book Access built-in documentation tools and improve your code. Discover how to make the best use of decorator and generator functions Enhance speed and improve concurrency by conjuring tricks from the PyPy project Who This Book Is For Whether you've been working with Python for a few years or you're a seasoned programmer, you'll have a lot of new tricks to walk away with. What You Will Learn Know the differences between .py and .pyc files Explore the different ways to install and upgrade Python packages Understand the working of the PyPI module that enhances built-in decorators See how coroutines are different from generators and how they can simulate multithreading Grasp how the decimal module improves floating point numbers and their operations Standardize sub interpreters to improve concurrency Discover Python's built-in docstring analyzer In Detail This book covers the unexplored secrets of Python, delve into its depths, and uncover its mysteries. You'll unearth secrets related to the implementation of the standard library, by looking at how modules actually work. You'll understand the implementation of collections, decimals, and fraction modules. If you haven't used decorators, coroutines, and generator functions much before, as you make your way through the recipes, you'll learn what you've been missing out on. We'll cover internal special methods in detail, so you understand what they are and how they can be used to improve the engineering decisions you make. Next, you'll explore the CPython interpreter, which is a treasure trove of secret hacks that not many programmers are aware of. We'll take you through the depths of the PyPy project, where you'll come across several exciting ways that you can improve speed and concurrency. Finally, we'll take time to explore the PEPs of the latest versions to discover some interesting hacks. Style and approach Recipe based approach where each problem is solved with the help of step by step instructions.
    Note: Description based on online resource; title from title page (Safari, viewed June 13, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788294874/?ar
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    Healthcare analytics made simple : techniques in healthcare computing using machine learning and Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787283220 , 1787283224
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Medical care ; Data processing ; Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Perform healthcare analytics with Python and SQL Build predictive models on real healthcare data with pandas and scikit-learn Use analytics to improve healthcare performance Book Description In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists' work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples. What you will learn Gain valuable insight into healthcare incentives, finances, and legislation Discover the connection between machine learning and healthcare processes Use SQL and Python to analyze data Measure healthcare quality and provider performance Identify features and attributes to build successful healthcare models Build predictive models using real-world healthcare data Become an expert in predictive modeling with structured clinical data See what lies ahead for healthcare analytics Who this book is for Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed August 27, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781787286702/?ar
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    IPython interactive computing and visualization cookbook : over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785881930 , 1785881930
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Command languages (Computer science) ; Information visualization ; Interactive computer systems ; Electronic books ; Electronic books ; local
    Abstract: Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. About This Book Leverage the Jupyter Notebook for interactive data science and visualization Become an expert in high-performance computing and visualization for data analysis and scientific modeling A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Who This Book Is For This book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods. What You Will Learn Master all features of the Jupyter Notebook Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments Visualize data and create interactive plots in the Jupyter Notebook Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn) Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV Simulate deterministic and stochastic dynamical systems in Python Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory In Detail Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform. IPython Interactive Computing and Visualization Cookbook, Second Edition contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning. The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed February 22, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781785888632/?ar
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    Practical convolutional neural networks : implement advanced deep learning models using Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Computer vision ; Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: One stop guide to implementing award-winning, and cutting-edge CNN architectures About This Book Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques Implement CNN models on image classification, transfer learning, Object Detection, Instance Segmentation, GANs and more Implement powerful use-cases like image captioning, reinforcement learning for hard attention, and recurrent attention models Who This Book Is For This book is for data scientists, machine learning and deep learning practitioners, Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected. What You Will Learn From CNN basic building blocks to advanced concepts understand practical areas they can be applied to Build an image classifier CNN model to understand how different components interact with each other, and then learn how to optimize it Learn different algorithms that can be applied to Object Detection, and Instance Segmentation Learn advanced concepts like attention mechanisms for CNN to improve prediction accuracy Understand transfer learning and implement award-winning CNN architectures like AlexNet, VGG, GoogLeNet, ResNet and more Understand the working of generative adversarial networks and how it can create new, unseen images In Detail Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available. Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms ...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (viewed April 2, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788392303/?ar
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    Machine Learning with scikit-learn quick start guide : classification, regression, and clustering techniques in Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789347371 , 1789347378
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering. Key Features Build your first machine learning model using scikit-learn Train supervised and unsupervised models using popular techniques such as classification, regression and clustering Understand how scikit-learn can be applied to different types of machine learning problems Book Description Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize, and evaluate all of the important machine learning algorithms that scikit-learn provides. This book teaches you how to use scikit-learn for machine learning. You will start by setting up and configuring your machine learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine learning models. You will learn classification, regression, and clustering techniques to work with different types of datasets and train your models. Finally, you will learn about an effective pipeline to help you build a machine learning project from scratch. By the end of this book, you will be confident in building your own machine learning models for accurate predictions. What you will learn Learn how to work with all scikit-learn's machine learning algorithms Install and set up scikit-learn to build your first machine learning model Employ Unsupervised Machine Learning Algorithms to cluster unlabelled data into groups Perform classification and regression machine learning Use an effective pipeline to build a machine learning project from scratch Who this book is for This book is for aspiring machine learning developers who want to get started with scikit-learn. Intermediate knowledge of Python programming and some fundamental knowledge of linear algebra and probability will help.
    Note: Description based on online resource; title from title page (viewed January 7, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789343700/?ar
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    Progressive web application development by example : develop fast, reliable, and engaging user experiences for the web (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787282346 , 1787282341
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Web applications ; Web site development ; Application software ; Development ; Application program interfaces (Computer software) ; Electronic books ; Electronic books ; local
    Abstract: Leverage the full potential of the web to make your web sites better than native applications for every platform. Key Features Explore different models and patterns required to develop progressive web applications Create applications requiring shorter runtime for attracting more users Study different projects to understand the fundamentals of progressive web applications Book Description Are you a developer that wants to create truly cross-platform user experiences with a minimal footprint, free of store restrictions and features customers want? Then you need to get to grips with Progressive Web Applications (PWAs), a perfect amalgamation of web and mobile applications with a blazing-fast response time. Progressive Web Application Development by Example helps you explore concepts of the PWA development by enabling you to develop three projects, starting with a 2048 game. In this game, you will review parts of a web manifest file and understand how a browser uses properties to define the home screen experience. You will then move on to learning how to develop and use a podcast client and be introduced to service workers. The application will demonstrate how service workers are registered and updated. In addition to this, you will review a caching API so that you have a firm understanding of how to use the cache within a service worker, and you'll discover core caching strategies and how to code them within a service worker. Finally, you will study how to build a tickets application, wherein you'll apply advanced service worker techniques, such as cache invalidation. Also, you'll learn about tools you can use to validate your applications and scaffold them for quality and consistency. By the end of the book, you will have walked through browser developer tools, node modules, and online tools for creating high-quality PWAs. What you will learn Explore the core principles of PWAs Study the three main technical requirements of PWAs Discover enhancing requirements to make PWAs transcend native apps and traditional websites Create and install PWAs on common websites with a given HTTPS as the core requirement Get acquainted with the service worker life cycle Define service worker caching patterns Apply caching strategies to three different website scenarios Implement best practices for web performance Who this book is for Progressive Web Application Development by Example is for you if you're a web developer or front-end designer who wants to ensure i...
    Note: Description based on online resource; title from title page (Safari, viewed September 19, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781787125421/?ar
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    Mastering Flask web development : build enterprise-grade, scalable Python web applications (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788999557 , 178899955X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Application software ; Development ; Web applications ; Web site development ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn to build modern, secure, highly available web MVC applications and API's using Python`s Flask framework. Key Features Create production-ready MVC and REST API with the dynamic features of Flask Utilize the various extensions like Flask-JWT and Flask-SQLAlchemy to develop powerful applications Deploy your flask application on real-world platforms like AWS and Heroku on VM's or Docker containers Book Description Flask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web Development will take you on a complete tour of the Flask environment and teach you how to build a production-ready application. You'll begin by learning about the installation of Flask and basic concepts such as MVC and accessing a database using an ORM. You will learn how to structure your application so that it can scale to any size with the help of Flask Blueprints. You'll then learn how to use Jinja2 templates with a high level of expertise. You will also learn how to develop with SQL or NoSQL databases, and how to develop REST APIs and JWT authentication. Next, you'll move on to build role-based access security and authentication using LDAP, OAuth, OpenID, and database. Also learn how to create asynchronous tasks that can scale to any load using Celery and RabbitMQ or Redis. You will also be introduced to a wide range of Flask extensions to leverage technologies such as cache, localization, and debugging. You will learn how to build your own Flask extensions, how to write tests, and how to get test coverage reports. Finally, you will learn how to deploy your application on Heroku and AWS using various technologies, such as Docker, CloudFormation, and Elastic Beanstalk, and will also learn how to develop Jenkins pipelines to build, test, and deploy applications. What you will learn Develop a Flask extension using best practices Implement various authentication methods: LDAP, JWT, Database, OAuth, and OpenID Learn how to develop role-based access security and become an expert on Jinja2 templates Build tests for your applications and APIs Install and configure a distributed task queue using Celery and RabbitMQ Develop RESTful APIs and secure REST API's Deploy highly available applications that scale on Heroku and AWS using Docker or VMs Who this book is for The ideal target audience for this book would be Python developers who want to use Flask and its advanced features to create Enterprise grade and lightweight applications. Th...
    Note: Previous edition published: 2015. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788995405/?ar
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    Mastering Linux shell scripting : a practical guide to Linux command- line, Bash scripting, and Shell programming (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788990158 , 1788990153
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Linux ; UNIX Shells ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Master the complexities of Bash shell scripting and unlock the power of shell for your enterprise About This Book Identify high-level steps such as verifying user input Using the command line and conditional statements in creating/executing simple shell scripts Create and edit dynamic shell scripts to manage complex and repetitive tasks Leverage the command-line to bypass GUI and automate common tasks Who This Book Is For If you are a Linux administrator or a system administrator and are interested in automating tasks in your daily lives, saving time and effort, this book is for you. Basic shell scripting and command-line experience will be required. Familiarity with the tasks you need to automate will be helpful. What You Will Learn Make, execute, and debug your first Bash script Create interactive scripts that prompt for user input Foster menu structures for operators with little command-line experience Develop scripts that dynamically edit web configuration files to produce a new virtual host Write scripts that use AWK to search and reports on log files Draft effective scripts using functions as building blocks, reducing maintenance and build time Make informed choices by comparing different script languages such as Python with BASH In Detail In this book, you'll discover everything you need to know to master shell scripting and make informed choices about the elements you employ. Grab your favorite editor and start writing your best Bash scripts step by step. Get to grips with the fundamentals of creating and running a script in normal mode, and in debug mode. Learn about various conditional statements' code snippets, and realize the power of repetition and loops in your shell script. You will also learn to write complex shell scripts. This book will also deep dive into file system administration, directories, and system administration like networking, process management, user authentications, and package installation and regular expressions. Towards the end of the book, you will learn how to use Python as a BASH Scripting alternative. By the end of this book, you will know shell scripts at the snap of your fingers and will be able to automate and communicate with your system with keyboard expressions. Style and approach The book will capture your attention and keep you engaged with the simplicity and clarity of each explanation. Every step is accompanied by screenshots so you can cross-check the results before moving on. Downloading the e...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 21, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788990554/?ar
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    Python GUI programming with Tkinter : develop responsive and powerful GUI applications with Tkinter (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788835688 , 1788835689
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Graphical user interfaces (Computer systems) ; Programming ; Python (Computer program language) ; Object-oriented programming (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Find out how to create visually stunning and feature-rich applications by empowering Python's built-in Tkinter GUI toolkit About This Book Explore Tkinter's powerful features to easily design and customize your GUI application Learn the basics of 2D and 3D animation in GUI applications. Learn to integrate stunning Data Visualizations using Tkinter Canvas and Matplotlib. Who This Book Is For This book will appeal to developers and programmers who would like to build GUI-based applications. Knowledge of Python is a prerequisite. What You Will Learn Implement the tools provided by Tkinter to design beautiful GUIs Discover cross-platform development through minor customizations in your existing application Visualize graphs in real time as data comes in using Tkinter's animation capabilities Use PostgreSQL authentication to ensure data security for your application Write unit tests to avoid regressions when updating code In Detail Tkinter is a lightweight, portable, and easy-to-use graphical toolkit available in the Python Standard Library, widely used to build Python GUIs due to its simplicity and availability. This book teaches you to design and build graphical user interfaces that are functional, appealing, and user-friendly using the powerful combination of Python and Tkinter. After being introduced to Tkinter, you will be guided step-by-step through the application development process. Over the course of the book, your application will evolve from a simple data-entry form to a complex data management and visualization tool while maintaining a clean and robust design. In addition to building the GUI, you'll learn how to connect to external databases and network resources, test your code to avoid errors, and maximize performance using asynchronous programming. You'll make the most of Tkinter's cross-platform availability by learning how to maintain compatibility, mimic platform-native look and feel, and build executables for deployment across popular computing platforms. By the end of this book, you will have the skills and confidence to design and build powerful high-end GUI applications to solve real-world problems. Style and approach This is a comprehensive guide that explores the essential Tkinter features and modules and implements them in building real-world cross-platform GUI applications Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://ww...
    Note: Description based on online resource; title from title page (Safari, viewed June 7, 2018)
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    Full-stack React projects : modern web development using React 16, Node, Express, and MongoDB (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788832946 , 1788832949
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Web site development ; Web sites ; Design ; Electronic books ; Electronic books ; local
    Abstract: Unleash the power of MERN stack by building diverse web applications using React, Node.js, Express, and MongoDB About This Book Create dynamic web applications with the MERN stack Leverage the power of React in building interactive and complex user interfaces Unlock the potential of Node, Express, and MongoDB to build modern full-stack applications Who This Book Is For Full-Stack React Web Development Projects is for JavaScript developers who have some experience with React, but no previous experience with full-stack development involving Node, Express, and MongoDB, and who want practical guidelines to start building different types of real-world web applications with this stack. What You Will Learn Set up your development environment and develop a MERN application Implement user authentication and authorization using JSON Web Tokens Build a social media application by extending the basic MERN application Create an online marketplace application with shopping cart and Stripe payments Develop a media streaming application using MongoDB GridFS Implement server-side rendering with data to improve SEO Set up and use React 360 to develop user interfaces with VR capabilities Learn industry best practices to make MERN stack applications reliable and scalable In Detail The benefits of using a full JavaScript stack for web development are undeniable, especially when robust and widely adopted technologies such as React, Node, and Express and are available. Combining the power of React with industry-tested, server-side technologies, such as Node, Express, and MongoDB, creates a diverse array of possibilities when developing real-world web applications. This book guides you through preparing the development environment for MERN stack-based web development, to creating a basic skeleton application and extending it to build four different web applications. These applications include a social media, an online marketplace, a media streaming, and a web-based game application with virtual reality features. While learning to set up the stack and developing a diverse range of applications with this book, you will grasp the inner workings of the MERN stack, extend its capabilities for complex features, and gain actionable knowledge of how to prepare MERN-based applications to meet the growing demands of real-world web applications. Style and approach This book provides practical guidelines on setting up and building MERN stack based applications, while providing f...
    Note: Description based on online resource; title from title page (Safari, viewed June 25, 2018)
    URL: lizenzpflichtig
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    Hands-on automated machine learning : a beginner's guide to building automated machine learning systems using AutoML and Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788622288 , 1788622286
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Automate data and model pipelines for faster machine learning applications About This Book Build automated modules for different machine learning components Understand each component of a machine learning pipeline in depth Learn to use different open source AutoML and feature engineering platforms Who This Book Is For If you're a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book is ideal for you. You'll also find this book useful if you're an ML engineer or data professional interested in developing quick machine learning pipelines for your projects. Prior exposure to Python programming will help you get the best out of this book. What You Will Learn Understand the fundamentals of Automated Machine Learning systems Explore auto-sklearn and MLBox for AutoML tasks Automate your preprocessing methods along with feature transformation Enhance feature selection and generation using the Python stack Assemble individual components of ML into a complete AutoML framework Demystify hyperparameter tuning to optimize your ML models Dive into Machine Learning concepts such as neural networks and autoencoders Understand the information costs and trade-offs associated with AutoML In Detail AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners' work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible. In this book, you'll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning. By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you'll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions. Style and approach Step by step approach to understand how to automate y...
    Note: Description based on online resource; title from title page (Safari, viewed May 23, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788629898/?ar
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    Node.js web development : server-side development with Node 10 made easy (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788627368 , 1788627369
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Fourth edition.
    Keywords: Node.js ; JavaScript (Computer program language) ; Web site development ; Electronic books ; Electronic books ; local
    Abstract: Create real-time applications using Node.js 10, Docker, MySQL, MongoDB, and Socket.IO with this practical guide and go beyond the developer's laptop to cover live deployment, including HTTPS and hardened security. About This Book Learn server-side JavaScript coding through the most up-to-date book on Node.js Explore the latest JavaScript features, and EcmaScript modules Walk through different stages of developing robust applications using Node.js 10 Who This Book Is For This book is for anybody looking for an alternative to the "P" languages (Perl, PHP, and Python), or anyone looking for a new paradigm of server-side application development. You should have at least a rudimentary understanding of JavaScript and web application development. What You Will Learn Install and use Node.js 10 for both development and deployment Use the Express 4.16 application framework Work with REST service development using the Restify framework Use data storage engines such as MySQL, SQLITE3, and MongoDB Use User authentication methods with OAuth2 Perform Real-time communication with the front-end using Socket.IO Implement Docker microservices in development, testing and deployment Perform unit testing with Mocha 5.x, and functional testing with Puppeteer 1.1.x Work with HTTPS using Let's Encrypt, and application security with Helmet In Detail Node.js is a server-side JavaScript platform using an event-driven, non-blocking I/O model allowing users to build fast and scalable data-intensive applications running in real time. This book gives you an excellent starting point, bringing you straight to the heart of developing web applications with Node.js. You will progress from a rudimentary knowledge of JavaScript and server-side development to being able to create, maintain, deploy and test your own Node.js application.You will understand the importance of transitioning to functions that return Promise objects, and the difference between fs, fs/promises and fs-extra. With this book you'll learn how to use the HTTP Server and Client objects, data storage with both SQL and MongoDB databases, real-time applications with Socket.IO, mobile-first theming with Bootstrap, microservice deployment with Docker, authenticating against third-party services using OAuth, and use some well known tools to beef up security of Express 4.16 applications. Style and approach Benefit from an easy, step-by-step approach that really works. Downloading the example code for this book You can d...
    Note: Description based on online resource; title from title page (Safari, viewed June 21, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788626859/?ar
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    Mastering the faster web with PHP, MySQL and JavaScript : develop state-of-the-art web applications using the latest web technologies (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788397711 , 1788397711
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: MySQL (Electronic resource) ; Web site development ; PHP (Computer program language) ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Make web applications run faster by using advanced PHP, SQL and JavaScript techniques About This Book Use a customized PHP stack to create efficient data-driven web applications Ensure seamless implementation of a JavaScript & HTML 5 CSS based frontend and PHP based backend. Learn about problem identification, best strategies, and UI design patterns as well to build a clean, fast web application Who This Book Is For The audience for this book would be PHP developers who have some basic knowledge of PHP programming and Web technologies. JavaScript programming knowledge is not necessary. What You Will Learn Install, confgure, and use profling and benchmarking testing tools Understand how to recognize optimizable data structures and functions to effectively optimize a PHP7 application Diagnose bad SQL query performance and discover ways to optimize it Grasp modern SQL techniques to optimize complex SQL queries Identify and simplify overly complex JavaScript code Explore and implement UI design principles that effectively enhance the performance Combine web technologies to boost web server performance In Detail This book will get you started with the latest benchmarking, profiling and monitoring tools for PHP, MySQL and JavaScript using Docker-based technologies. From optimizing PHP 7 code to learning asynchronous programming, from implementing Modern SQL solutions to discovering Functional JavaScript techniques, this book covers all the latest developments in Faster Web technologies. You will not only learn to determine the best optimization strategies, but also how to implement them. Along the way, you will learn how to profile your PHP scripts with Blackfire.io, monitor your Web applications, measure database performance, optimize SQL queries, explore Functional JavaScript, boost Web server performance in general and optimize applications when there is nothing left to optimize by going beyond performance. After reading this book, you will know how to boost the performance of any Web application and make it part of what has come to be known as the Faster Web. Style and approach The book has a step by step practical approach to developing highly efficient Web applications, with many practical and useful code snippets.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed July 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788392211/?ar
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    Data-centric applications with Vaadin 8 : develop and maintain high-quality web applications using Vaadin (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781783288854 , 178328885X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Application software Development ; Web site development
    Note: Description based on online resource; title from title page (Safari, viewed May 30, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781783288847/?ar
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    Python 3 object-oriented programming : build robust and maintainable software with object-oriented design patterns in Python 3.8 (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789617078 , 1789617073
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Python (Computer program language) ; Object-oriented programming (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Uncover modern Python with this guide to Python data structures, design patterns, and effective object-oriented techniques Key Features In-depth analysis of many common object-oriented design patterns that are more suitable to Python's unique style Learn the latest Python syntax and libraries Explore abstract design patterns and implement them in Python 3.8 Book Description Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. This third edition of Python 3 Object-Oriented Programming fully explains classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software. Starting with a detailed analysis of object-oriented programming, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. You will learn how to create maintainable applications by studying higher level design patterns. The book will show you the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems, unittest and pytest, will be introduced in this book. You'll get a comprehensive introduction to Python's concurrent programming ecosystem. By the end of the book, you will have thoroughly learned object-oriented principles using Python syntax and be able to create robust and reliable programs confidently. What you will learn Implement objects in Python by creating classes and defining methods Grasp common concurrency techniques and pitfalls in Python 3 Extend class functionality using inheritance Understand when to use object-oriented features, and more importantly when not to use them Discover what design patterns are and why they are different in Python Uncover the simplicity of unit testing and why it's so important in Python Explore concurrent object-oriented programming Who this book is for If you're new to object-oriented programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply OOP in Python, this is the book for you. If you are an object-oriented programmer for other languages or seeking a leg up in the new world of Python 3.8, you too will find this book a useful introduction to Python. Previous experience with Python 3 is not necessary.
    Note: Description based on online resource; title from title page (viewed January 8, 2019)
    URL: lizenzpflichtig
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    Hands-on cryptography with Python : leverage the power of Python to encrypt and decrypt data (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789537949 , 1789537940
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Cryptography ; Ciphers ; Data encryption (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Learn to evaluate and compare data encryption methods and attack cryptographic systems About This Book Explore popular and important cryptographic methods Compare cryptographic modes and understand their limitations Learn to perform attacks on cryptographic systems Who This Book Is For Hands-On Cryptography with Python is for security professionals who want to learn to encrypt and evaluate data, and compare different encryption methods. What You Will Learn Protect data with encryption and hashing Explore and compare various encryption methods Encrypt data using the Caesar Cipher technique Make hashes and crack them Learn how to use three NIST-recommended systems: AES, SHA, and RSA Understand common errors in encryption and exploit them In Detail Cryptography is essential for protecting sensitive information, but it is often performed inadequately or incorrectly. Hands-On Cryptography with Python starts by showing you how to encrypt and evaluate your data. The book will then walk you through various data encryption methods,such as obfuscation, hashing, and strong encryption, and will show how you can attack cryptographic systems. You will learn how to create hashes, crack them, and will understand why they are so different from each other. In the concluding chapters, you will use three NIST-recommended systems: the Advanced Encryption Standard (AES), the Secure Hash Algorithm (SHA), and the Rivest-Shamir-Adleman (RSA). By the end of this book, you will be able to deal with common errors in encryption. Style and approach A practical guide that will help the readers to encrypt their data with ease
    Note: Description based on online resource; title from title page (Safari, viewed August 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789534443/?ar
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    Deep learning with PyTorch quick start guide : learn to train and deploy neural network models in Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789539738 , 1789539730
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Machine learning ; Python (Computer program language) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing. Key Features Clear and concise explanations Gives important insights into deep learning models Practical demonstration of key concepts Book Description PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. What you will learn Set up the deep learning environment using the PyTorch library Learn to build a deep learning model for image classification Use a convolutional neural network for transfer learning Understand to use PyTorch for natural language processing Use a recurrent neural network to classify text Understand how to optimize PyTorch in multiprocessor and distributed environments Train, optimize, and deploy your neural networks for maximum accuracy and performance Learn to deploy production-ready models Who this book is for Developers and Data Scientist familiar with Machine Learning but new to deep learning, or existing practitioners of deep learning who would like to use PyTorch to train their deep learning models will find this book to be useful. Having knowledge of Python programming will be an added advantage, while previous exposure to PyTorch is not needed.
    Note: Description based on online resource; title from title page (viewed February 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789534092/?ar
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    WordPress development quick start guide : build beautiful and dynamic websites for your domain from scratch (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789342581 , 1789342589
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: WordPress (Electronic resource) ; Web site development ; Application software ; Development ; Web sites ; Design ; Electronic books ; Electronic books ; local
    Abstract: Learn core WordPress concepts and components to create modern WordPress-based solutions Key Features Learn the foundations of WordPress development and its hook-based architecture Choose the right components for any development task Build flexible solutions that works with existing plugins and themes Book Description WordPress is the most used CMS in the world and is the ideal way to share your knowledge with a large audience or build a profitable business. Getting started with WordPress development has often been a challenge for novice developers, and this book will help you find your way. This book explains the components used in WordPress development, when and where to use them, and why you should be using each component in specific scenarios. You begin by learning the basic development setup and coding standards of WordPress. Then you move into the most important aspects of the theme and plugin development process. Here you will also learn how themes and plugins fit into the website while learning about a range of techniques for extending themes and plugins. With the basics covered, we explore many of the APIs provided by WordPress and how we can leverage them to build rapid solutions. Next, we move on to look at the techniques for capturing, processing, and displaying user data when integrating third-party components into the site design. Finally, you will learn how to test and deploy your work with secure and maintainable code, while providing the best performance for end users. What you will learn Explore the role of themes, plugins, and built-in features in development Adapt to built-in modules and built-in database structures Write code for WordPress's hook-based architecture Build, customize, and integrate WordPress plugins Extend themes with custom design templates Capture and process data with built-in features and custom forms Improve usability with AJAX and third-party components Manage non-functional aspects, such as security, performance, and migration Who this book is for This book is for web developers and site owners who want to build custom websites with WordPress. Basic knowledge of PHP, JavaScript, HTML and CSS is required to get most out of this book.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed December 11, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789342871/?ar
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    Hands-on predictive analytics with Python : master the complete predictive analytics process, from problem definition to model deployment (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789134544 , 1789134544
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Decision making ; Data processing ; Data mining ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Step-by-step guide to build high performing predictive applications Key Features Use the Python data analytics ecosystem to implement end-to-end predictive analytics projects Explore advanced predictive modeling algorithms with an emphasis on theory with intuitive explanations Learn to deploy a predictive model's results as an interactive application Book Description Predictive analytics is an applied field that employs a variety of quantitative methods using data to make predictions. It involves much more than just throwing data onto a computer to build a model. This book provides practical coverage to help you understand the most important concepts of predictive analytics. Using practical, step-by-step examples, we build predictive analytics solutions while using cutting-edge Python tools and packages. The book's step-by-step approach starts by defining the problem and moves on to identifying relevant data. We will also be performing data preparation, exploring and visualizing relationships, building models, tuning, evaluating, and deploying model. Each stage has relevant practical examples and efficient Python code. You will work with models such as KNN, Random Forests, and neural networks using the most important libraries in Python's data science stack: NumPy, Pandas, Matplotlib, Seaborn, Keras, Dash, and so on. In addition to hands-on code examples, you will find intuitive explanations of the inner workings of the main techniques and algorithms used in predictive analytics. By the end of this book, you will be all set to build high-performance predictive analytics solutions using Python programming. What you will learn Get to grips with the main concepts and principles of predictive analytics Learn about the stages involved in producing complete predictive analytics solutions Understand how to define a problem, propose a solution, and prepare a dataset Use visualizations to explore relationships and gain insights into the dataset Learn to build regression and classification models using scikit-learn Use Keras to build powerful neural network models that produce accurate predictions Learn to serve a model's predictions as a web application Who this book is for This book is for data analysts, data scientists, data engineers, and Python developers who want to learn about predictive modeling and would like to implement predictive analytics solutions using Python's data stack. People from other backgrounds who would like to enter this excitin...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 26, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789138719/?ar
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    Recurrent neural networks with Python Quick Start Guide : sequential learning and language modeling with TensorFlow (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789133660 , 1789133661
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn how to develop intelligent applications with sequential learning and apply modern methods for language modeling with neural network architectures for deep learning with Python's most popular TensorFlow framework. Key Features Train and deploy Recurrent Neural Networks using the popular TensorFlow library Apply long short-term memory units Expand your skills in complex neural network and deep learning topics Book Description Developers struggle to find an easy-to-follow learning resource for implementing Recurrent Neural Network (RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve results. This book will teach you the fundamentals of RNNs, with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling. Your journey starts with the simplest RNN model, where you can grasp the fundamentals. The book then builds on this by proposing more advanced and complex algorithms. We use them to explain how a typical state-of-the-art RNN model works. From generating text to building a language translator, we show how some of today's most powerful AI applications work under the hood. After reading the book, you will be confident with the fundamentals of RNNs, and be ready to pursue further study, along with developing skills in this exciting field. What you will learn Use TensorFlow to build RNN models Use the correct RNN architecture for a particular machine learning task Collect and clear the training data for your models Use the correct Python libraries for any task during the building phase of your model Optimize your model for higher accuracy Identify the differences between multiple models and how you can substitute them Learn the core deep learning fundamentals applicable to any machine learning model Who this book is for This book is for Machine Learning engineers and data scientists who want to learn about Recurrent Neural Network models with practical use-cases. Exposure to Python programming is required. Previous experience with TensorFlow will be helpful, but not mandatory.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (viewed February 5, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789132335/?ar
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    TensorFlow machine learning cookbook : over 60 recipes to build intelligent machine learning systems with the power of Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789130768 , 178913076X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Machine learning ; Artificial intelligence ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Skip the theory and get the most out of Tensorflow to build production-ready machine learning models Key Features Exploit the features of Tensorflow to build and deploy machine learning models Train neural networks to tackle real-world problems in Computer Vision and NLP Handy techniques to write production-ready code for your Tensorflow models Book Description TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios. What you will learn Become familiar with the basic features of the TensorFlow library Get to know Linear Regression techniques with TensorFlow Learn SVMs with hands-on recipes Implement neural networks to improve predictive modeling Apply NLP and sentiment analysis to your data Master CNN and RNN through practical recipes Implement the gradient boosted random forest to predict housing prices Take TensorFlow into production Who this book is for If you are a data scientist or a machine learning engineer with some knowledge of linear algebra, statistics, and machine learning, this book is for you. If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading pages and pages of material, this book is for you. Some background in Python programming is assumed. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/s...
    Note: Previous edition published: 2017. - Description based on online resource; title from title page (Safari, viewed October 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789131680/?ar
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    Natural language processing with Python quick start guide : going from a Python developer to an effective natural language processing engineer (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788994101 , 1788994108
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Natural language processing (Computer science) ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learning Key Features A no-math, code-driven programmer's guide to text processing and NLP Get state of the art results with modern tooling across linguistics, text vectors and machine learning Fundamentals of NLP methods from spaCy, gensim, scikit-learn and PyTorch Book Description NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP. The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a work?ow for building NLP applications. We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn. We conclude by deploying these models as REST APIs with Flask. By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges. What you will learn Understand classical linguistics in using English grammar for automatically generating questions and answers from a free text corpus Work with text embedding models for dense number representations of words, subwords and characters in the English language for exploring document clustering Deep Learning in NLP using PyTorch with a code-driven introduction to PyTorch Using an NLP project management Framework for estimating timelines and organizing your project into stages Hack and build a simple chatbot application in 30 minutes Deploy an NLP or machine learning application using Flask as RESTFUL APIs Who this book is for Programmers who wish to build systems that can interpret language. Exposure to Python programming is required. Familiarity with NLP or machine learning vocabulary will be helpful, but not mandatory.
    Note: Description based on online resource; title from title page (viewed February 5, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789130386/?ar
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    Hands-on natural language processing with Python : a practical guide to applying deep learning architectures to your NLP applications (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789135916 , 1789135915
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Natural language processing (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Foster your NLP applications with the help of deep learning, NLTK, and TensorFlow Key Features Weave neural networks into linguistic applications across various platforms Perform NLP tasks and train its models using NLTK and TensorFlow Boost your NLP models with strong deep learning architectures such as CNNs and RNNs Book Description Natural language processing (NLP) has found its application in various domains, such as web search, advertisements, and customer services, and with the help of deep learning, we can enhance its performances in these areas. Hands-On Natural Language Processing with Python teaches you how to leverage deep learning models for performing various NLP tasks, along with best practices in dealing with today's NLP challenges. To begin with, you will understand the core concepts of NLP and deep learning, such as Convolutional Neural Networks (CNNs), recurrent neural networks (RNNs), semantic embedding, Word2vec, and more. You will learn how to perform each and every task of NLP using neural networks, in which you will train and deploy neural networks in your NLP applications. You will get accustomed to using RNNs and CNNs in various application areas, such as text classification and sequence labeling, which are essential in the application of sentiment analysis, customer service chatbots, and anomaly detection. You will be equipped with practical knowledge in order to implement deep learning in your linguistic applications using Python's popular deep learning library, TensorFlow. By the end of this book, you will be well versed in building deep learning-backed NLP applications, along with overcoming NLP challenges with best practices developed by domain experts. What you will learn Implement semantic embedding of words to classify and find entities Convert words to vectors by training in order to perform arithmetic operations Train a deep learning model to detect classification of tweets and news Implement a question-answer model with search and RNN models Train models for various text classification datasets using CNN Implement WaveNet a deep generative model for producing a natural-sounding voice Convert voice-to-text and text-to-voice Train a model to convert speech-to-text using DeepSpeech Who this book is for Hands-on Natural Language Processing with Python is for you if you are a developer, machine learning or an NLP engineer who wants to build a deep learning application that leverages NLP techniques. This comprehen...
    Note: Description based on online resource; title from title page (Safari, viewed August 14, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789139495/?ar
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    Keras deep learning cookbook : over 30 recipes for implementing deep neural networks in Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788623087 , 1788623088
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of deep learning and Keras to develop smarter and more efficient data models Key Features Understand different neural networks and their implementation using Keras Explore recipes for training and fine-tuning your neural network models Put your deep learning knowledge to practice with real-world use-cases, tips, and tricks Book Description Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy. The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks. By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning What you will learn Install and configure Keras in TensorFlow Master neural network programming using the Keras library Understand the different Keras layers Use Keras to implement simple feed-forward neural networks, CNNs and RNNs Work with various datasets and models used for image and text classification Develop text summarization and reinforcement learning models using Keras Who this book is for Keras Deep Learning Cookbook is for you if you are a data scientist or machine learning expert who wants to find practical solutions to common problems encountered while training deep learning models. A basic understanding of Python and some experience in machine learning and neural networks is required for this book.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 11, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788621755/?ar
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    Modern Python standard library cookbook : over 100 recipes to fully leverage the features of the standard library in Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788833295 , 1788833295
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Build optimized applications in Python by smartly implementing the standard library Key Features Strategic recipes for effective application development in Python Techniques to create GUIs and implement security through cryptography Best practices for developing readily scalable, production-ready applications Book Description The Python 3 Standard Library is a vast array of modules that you can use for developing various kinds of applications. It contains an exhaustive list of libraries, and this book will help you choose the best one to address specific programming problems in Python. The Modern Python Standard Library Cookbook begins with recipes on containers and data structures and guides you in performing effective text management in Python. You will find Python recipes for command-line operations, networking, filesystems and directories, and concurrent execution. You will learn about Python security essentials in Python and get to grips with various development tools for debugging, benchmarking, inspection, error reporting, and tracing. The book includes recipes to help you create graphical user interfaces for your application. You will learn to work with multimedia components and perform mathematical operations on date and time. The recipes will also show you how to deploy different searching and sorting algorithms on your data. By the end of the book, you will have acquired the skills needed to write clean code in Python and develop applications that meet your needs. What you will learn Store multiple values per key in associative containers Create interactive character-based user interfaces Work with native time and display data for your time zone Read/write SGML family languages, both as a SAX and DOM parser to meet file sizes and other requirements Group equivalent items using itertools and sorted features together Use partials to create unary functions out of multi-argument functions Implement hashing algorithms to store passwords in a safe way Who this book is for If you are a developer who wants to write highly responsive, manageable, scalable, and resilient code in Python, this book is for you. Prior programming knowledge in Python will help you make the most out of the book.
    Note: Description based on online resource; title from title page (Safari, viewed October 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788830829/?ar
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    Learning robotics using Python : design, simulate, program, and prototype an autonomous mobile robot using ROS, OpenCV, PCL, and Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788629973 , 1788629973
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Robotics ; Automation ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Design, simulate, and program interactive robots About This Book Design, simulate, build, and program an interactive autonomous mobile robot Leverage the power of ROS, Gazebo, and Python to enhance your robotic skills A hands-on guide to creating an autonomous mobile robot with the help of ROS and Python Who This Book Is For This book is for those who are conducting research in mobile robotics and autonomous navigation. As well as the robotics research domain, this book is also for the robot hobbyist community. You're expected to have a basic understanding of Linux commands and Python. What You Will Learn Design a differential robot from scratch Model a differential robot using ROS and URDF Simulate a differential robot using ROS and Gazebo Design robot hardware electronics Interface robot actuators with embedded boards Explore the interfacing of different 3D depth cameras in ROS Implement autonomous navigation in ChefBot Create a GUI for robot control In Detail Robot Operating System (ROS) is one of the most popular robotics software frameworks in research and industry. It has various features for implementing different capabilities in a robot without implementing them from scratch. This book starts by showing you the fundamentals of ROS so you understand the basics of differential robots. Then, you'll learn about robot modeling and how to design and simulate it using ROS. Moving on, we'll design robot hardware and interfacing actuators. Then, you'll learn to configure and program depth sensors and LIDARs using ROS. Finally, you'll create a GUI for your robot using the Qt framework. By the end of this tutorial, you'll have a clear idea of how to integrate and assemble everything into a robot and how to bundle the software package. Style and approach A step-by-step guide which will help you to create an autonomous mobile robot with the help of ROS and Python. It will help you to understand and implement the fundamental concepts of differential robots and teach you to create differential robot's simulation using Gazebo.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed July 24, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788623315/?ar
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    Python artificial intelligence projects for beginners : get up and running with artificial intelligence using 8 smart and exciting AI applications (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789538243 , 1789538246
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Artificial intelligence ; Data processing ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Build smart applications by implementing real-world artificial intelligence projects Key Features Explore a variety of AI projects with Python Get well-versed with different types of neural networks and popular deep learning algorithms Leverage popular Python deep learning libraries for your AI projects Book Description Artificial Intelligence (AI) is the newest technology that's being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence. This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library. By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress What you will learn Build a prediction model using decision trees and random forest Use neural networks, decision trees, and random forests for classification Detect YouTube comment spam with a bag-of-words and random forests Identify handwritten mathematical symbols with convolutional neural networks Revise the bird species identifier to use images Learn to detect positive and negative sentiment in user reviews Who this book is for Python Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you're able to play around with code Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Description based on online resource; title from title page (Safari, viewed August 28, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789539462/?ar
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    Pytest quick start guide : write better Python code with simple and maintainable tests (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789343823 , 1789343828
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Computer software ; Testing ; Debugging in computer science ; Electronic books ; Electronic books ; local
    Abstract: Learn the pytest way to write simple tests which can also be used to write complex tests Key Features Become proficient with pytest from day one by solving real-world testing problems Use pytest to write tests more efficiently Scale from simple to complex and functional testing Book Description Python's standard unittest module is based on the xUnit family of frameworks, which has its origins in Smalltalk and Java, and tends to be verbose to use and not easily extensible.The pytest framework on the other hand is very simple to get started, but powerful enough to cover complex testing integration scenarios, being considered by many the true Pythonic approach to testing in Python. In this book, you will learn how to get started right away and get the most out of pytest in your daily work?ow, exploring powerful mechanisms and plugins to facilitate many common testing tasks. You will also see how to use pytest in existing unittest-based test suites and will learn some tricks to make the jump to a pytest-style test suite quickly and easily. What you will learn Write and run simple and complex tests Organize tests in fles and directories Find out how to be more productive on the command line Markers and how to skip, xfail and parametrize tests Explore fxtures and techniques to use them effectively, such as tmpdir, pytestconfg, and monkeypatch Convert unittest suites to pytest using little-known techniques Use third-party plugins Who this book is for This book is for Python programmers that want to learn more about testing. This book is also for QA testers, and those who already benefit from programming with tests daily but want to improve their existing testing tools.
    Note: Description based on online resource; title from title page (Safari, viewed September 20, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789347562/?ar
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    Python penetration testing essentials : techniques for ethical hacking with Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789136043 , 1789136040
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Penetration testing (Computer security) ; Electronic books ; Electronic books ; local
    Abstract: This book gives you the skills you need to use Python for penetration testing, with the help of detailed code examples. This book has been updated for Python 3.6.3 and Kali Linux 2018.1. About This Book Detect and avoid various attack types that put the privacy of a system at risk Leverage Python to build efficient code and eventually build a robust environment Learn about securing wireless applications and information gathering on a web server Who This Book Is For If you are a Python programmer, a security researcher, or an ethical hacker and are interested in penetration testing with the help of Python, then this book is for you. Even if you are new to the field of ethical hacking, this book can help you find the vulnerabilities in your system so that you are ready to tackle any kind of attack or intrusion. What You Will Learn The basics of network pentesting including network scanning and sniffing Wireless, wired attacks, and building traps for attack and torrent detection Web server footprinting and web application attacks, including the XSS and SQL injection attack Wireless frames and how to obtain information such as SSID, BSSID, and the channel number from a wireless frame using a Python script The importance of web server signatures, email gathering, and why knowing the server signature is the first step in hacking In Detail This book gives you the skills you need to use Python for penetration testing (pentesting), with the help of detailed code examples. We start by exploring the basics of networking with Python and then proceed to network hacking. Then, you will delve into exploring Python libraries to perform various types of pentesting and ethical hacking techniques. Next, we delve into hacking the application layer, where we start by gathering information from a website. We then move on to concepts related to website hacking - such as parameter tampering, DDoS, XSS, and SQL injection. By reading this book, you will learn different techniques and methodologies that will familiarize you with Python pentesting techniques, how to protect yourself, and how to create automated programs to find the admin console, SQL injection, and XSS attacks. Style and approach The book starts at a basic level and moves to a higher level of network and web security. The execution and performance of code are both taken into account.
    Note: Description based on online resource; title from title page (Safari, viewed June 20, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789138962/?ar
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    Python automation cookbook : explore the world of automation using Python recipes that will enhance your skills (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788999151 , 1788999150
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic data processing ; Automation ; Electronic books ; Electronic books ; local
    Abstract: Step-by-step instructions which take you through each program to automate monotonous tasks with Python 3.7 Key Features Automate integral business processes such as report generation, email marketing, and lead generation Build your first web application that scrapes data and accesses websites' APIs Create graphic-rich charts, graphs, and maps using Matplotlib Book Description Have you been doing the same old monotonous office work over and over again? Or have you been trying to find an easy way to make your life better by automating some of your repetitive tasks? Through a tried and tested approach, understand how to automate all the boring stuff using Python. The Python Automation Cookbook helps you develop a clear understanding of how to automate your business processes using Python, including detecting opportunities by scraping the web, analyzing information to generate automatic spreadsheets reports with graphs, and communicating with automatically generated emails. You'll learn how to get notifications via text messages and run tasks while your mind is focused on other important activities, followed by understanding how to scan documents such as resumes. Once you've gotten familiar with the fundamentals, you'll be introduced to the world of graphs, along with studying how to produce organized charts using Matplotlib. In addition to this, you'll gain in-depth knowledge of how to generate rich graphics showing relevant information. By the end of this book, you'll have refined your skills by attaining a sound understanding of how to identify and correct problems to produce superior and reliable systems. What you will learn Get to grips with scraping a website to detect changes Search and process raw sales files to aggregate information in spreadsheets Explore techniques to extract information from an Excel spreadsheet and generate exciting reports with graphs Discover the techniques required to generate random, print-friendly codes to be used as single-use coupons Automatically generate a marketing campaign, contacting the recipients over different channels Identify and implement precise solutions Who this book is for The Python Automation Cookbook is for you if you are a developer or anyone who wants to automate monotonous manual tasks related to fields such as finance, sales, and HR, among others. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at h...
    Note: Description based on online resource; title from title page (Safari, viewed October 22, 2018)
    URL: lizenzpflichtig
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    Modern JavaScript web development cookbook : easy solutions to common and everyday JavaScript development problems (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788992350 , 1788992350
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Web site development ; Web sites ; Design ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Over 90 recipes to help you write clean code, solve common JavaScript problems, and work on popular use cases like SPAs, microservices, native mobile development with Node, React, React Native and Electron. Key Features Over 90 practical recipes to help you write clean and maintainable JavaScript codes with the latest ES8 Leverage the power of leading web frameworks like Node and React to build modern web apps Features comprehensive coverage of tools and techniques needed to create multi-platform apps with JavaScript Book Description JavaScript has evolved into a language that you can use on any platform. Modern JavaScript Web Development Cookbook is a perfect blend of solutions for traditional JavaScript development and modern areas that developers have lately been exploring with JavaScript. This comprehensive guide teaches you how to work with JavaScript on servers, browsers, mobile phones and desktops. You will start by exploring the new features of ES8. You will then move on to learning the use of ES8 on servers (with Node.js), with the objective of producing services and microservices and dealing with authentication and CORS. Once you get accustomed to ES8, you will learn to apply it to browsers using frameworks, such as React and Redux, which interact through Ajax with services. You will then understand the use of a modern framework to develop the UI. In addition to this, development for mobile devices with React Native will walk you through the benefits of creating native apps, both for Android and iOS. Finally, you'll be able to apply your new-found knowledge of server-side and client-side tools to develop applications with Electron. What you will learn Use the latest features of ES8 and learn new ways to code with JavaScript Develop server-side services and microservices with Node.js Learn to do unit testing and to debug your code Build client-side web applications using React and Redux Create native mobile applications for Android and iOS with React Native Write desktop applications with Electron Who this book is for This book is for developers who want to explore the latest JavaScript features, frameworks, and tools for building complete mobile, desktop and web apps, including server and client-side code. You are expected to have working knowledge of JavaScript to get the most out of this book.
    Note: Description based on online resource; title from title page (Safari, viewed February 22, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788992749/?ar
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    Learning Python web penetration testing : automate web penetration testing activities using Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789539677 , 1789539676
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Python (Computer program language) ; Penetration testing (Computer security) ; Computer networks Security measures
    Note: Description based on online resource; title from title page (Safari, viewed July 23, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781789533972/?ar
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    Natural language processing with TensorFlow : teach language to machines using Python's deep learning library (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788477758 , 1788477758
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    RVK:
    ST 250
    RVK:
    ST 306
    Keywords: Natural language processing (Computer science) ; Machine learning ; Python (Computer program language) ; TensorFlow ; Sprachverarbeitung ; Sprachverarbeitung ; TensorFlow
    Note: Description based on online resource; title from title page (Safari, viewed June 27, 2018). - Includes index
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788478311/?ar
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    Computer vision projects with OpenCV and Python 3 : six end-to-end projects build using machine learning with OpenCV, Python, and TensorFlow (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789954906 , 1789954908
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: OpenCV (Computer program language) ; Computer vision ; Python (Computer program language) ; Image processing ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Gain a working knowledge of advanced machine learning and explore Python's powerful tools for extracting data from images and videos Key Features Implement image classification and object detection using machine learning and deep learning Perform image classification, object detection, image segmentation, and other Computer Vision tasks Crisp content with a practical approach to solving real-world problems in Computer Vision Book Description Python is the ideal programming language for rapidly prototyping and developing production-grade codes for image processing and Computer Vision with its robust syntax and wealth of powerful libraries. This book will help you design and develop production-grade Computer Vision projects tackling real-world problems. With the help of this book, you will learn how to set up Anaconda and Python for the major OSes with cutting-edge third-party libraries for Computer Vision. You'll learn state-of-the-art techniques for classifying images, finding and identifying human postures, and detecting faces within videos. You will use powerful machine learning tools such as OpenCV, Dlib, and TensorFlow to build exciting projects such as classifying handwritten digits, detecting facial features,and much more. The book also covers some advanced projects, such as reading text from license plates from real-world images using Google's Tesseract software, and tracking human body poses using DeeperCut within TensorFlow. By the end of this book, you will have the expertise required to build your own Computer Vision projects using Python and its associated libraries. What you will learn Install and run major Computer Vision packages within Python Apply powerful support vector machines for simple digit classification Understand deep learning with TensorFlow Build a deep learning classifier for general images Use LSTMs for automated image captioning Read text from real-world images Extract human pose data from images Who this book is for Python programmers and machine learning developers who wish to build exciting Computer Vision projects using the power of machine learning and OpenCV will find this book useful. The only prerequisite for this book is that you should have a sound knowledge of Python programming.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 26, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789954555/?ar
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    Artificial intelligence and machine learning fundamentals (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789809206 , 1789809207
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Artificial intelligence ; Neural networks (Computer science) ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Create AI applications in Python and lay the foundations for your career in data science Key Features Practical examples that explain key machine learning algorithms Explore neural networks in detail with interesting examples Master core AI concepts with engaging activities Book Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! What you will learn Understand the importance, principles, and fields of AI Implement basic artificial intelligence concepts with Python Apply regression and classification concepts to real-world problems Perform predictive analysis using decision trees and random forests Carry out clustering using the k-means and mean shift algorithms Understand the fundamentals of deep learning via practical examples Who this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it's recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
    Note: Description based on online resource; title from copyright page (Safari, viewed February 11, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789801651/?ar
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    Drupal 8 quick start guide : get up and running with Drupal 8 (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789342932 , 1789342937
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Drupal (Computer file) ; Web sites ; Authoring programs ; Web site development ; Electronic books ; Electronic books ; local
    Abstract: Your step by step guide with easy to follow instructions for navigating Drupal 8 Key Features Build a great Drupal website easily How to structure, create and maintain different types of content Design roles for secure editing of your site Book Description Drupal is a powerful content management platform, ?exible enough to accommodate almost any content requirements. This ?exibility comes with a cost: complexity. Drupal 8 Quick Start Guide will clear your path from installation to a building usable site in minutes, and to a customized site in one sitting. You will begin with installation of Drupal and going through the main sections of the Drupal UI. Then, you will create a content type that describes its content, which simplifies the act of creating and editing the actual content later. You will learn about user roles, using real-world examples. This will help you to learn how to design roles, and how to assign appropriate permissions to them. Next, you will learn to use the WYSIWYG editor, configure it for other roles, navigate the various fields on the content creation form, and publish content. To begin to appreciate the ?exibility and expandability of Drupal, you will make use of popular content-focused modules that extend Drupal's power. You will learn how to expand your market to other readers directly and through other sites by configuring content and UI translations and creating a View that provides an RSS feed. Finally, you will put everything together by customizing the home page for your new website. What you will learn Create and customize Drupal structures, such as menus, tags, and content categories Extend Drupal's capabilities with add-on modules Administer site users, their roles, and the actions to which they are granted access Understand user roles and permissions Create, edit, and publish content Use Views for custom content selection and display Expand your audience with custom RSS feeds Configure a home page with meaningful sections for a better UX Who this book is for This book is for content administrators, developers, site builders and administrators who are new to Drupal 8.
    Note: Description based on online resource; title from title page (viewed January 7, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789340310/?ar
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    Hands-on reactive programming with Python : event-driven development unraveled with RxPY (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789132755 , 1789132754
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: A comprehensive guide to help you understand the principles of Reactive and asynchronous programming and its benefits Key Features Explore the advantages of Reactive programming Use concurrency and parallelism in RxPY to build powerful reactive applications Deploy and scale your reactive applications using Docker Book Description Reactive programming is central to many concurrent systems, but it's famous for its steep learning curve, which makes most developers feel like they're hitting a wall. With this book, you will get to grips with reactive programming by steadily exploring various concepts This hands-on guide gets you started with Reactive Programming (RP) in Python. You will learn abouta the principles and benefits of using RP, which can be leveraged to build powerful concurrent applications. As you progress through the chapters, you will be introduced to the paradigm of Functional and Reactive Programming (FaRP), observables and observers, and concurrency and parallelism. The book will then take you through the implementation of an audio transcoding server and introduce you to a library that helps in the writing of FaRP code. You will understand how to use third-party services and dynamically reconfigure an application. By the end of the book, you will also have learned how to deploy and scale your applications with Docker and Traefik and explore the significant potential behind the reactive streams concept, and you'll have got to grips with a comprehensive set of best practices. What you will learn Structure Python code for better readability, testing, and performance Explore the world of event-based programming Grasp the use of the most common operators in Rx Understand reactive extensions beyond simple examples Master the art of writing reusable components Deploy an application on a cloud platform with Docker and Traefik Who this book is for If you are a Python developer who wants to learn Reactive programming to build powerful concurrent and asynchronous applications, this book is for you. Basic understanding of the Python language is all you need to understand the concepts covered in this book.
    Note: Description based on online resource; title from title page (Safari, viewed December 3, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789138726/?ar
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    Mastering Python networking : your one-stop solution to using Python for network automation, DevOps, and test-driven development (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789130263 , 1789130263
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Application software ; Development ; Computer networks ; Management ; Electronic books ; Electronic books ; local
    Abstract: Master the art of using Python for a diverse range of network engineering tasks Key Features Explore the power of Python libraries to tackle difficult network problems efficiently and effectively Use Python for network device automation, DevOps, and software-defined networking Become an expert in implementing advanced network-related tasks with Python Book Description Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In this second edition of Mastering Python Networking, you'll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This book begins by reviewing the basics of Python and teaches you how Python can interact with both legacy and API-enabled network devices. As you make your way through the chapters, you will then learn to leverage high-level Python packages and frameworks to perform network engineering tasks for automation, monitoring, management, and enhanced security. In the concluding chapters, you will use Jenkins for continuous network integration as well as testing tools to verify your network. By the end of this book, you will be able to perform all networking tasks with ease using Python. What you will learn Use Python libraries to interact with your network Integrate Ansible 2.5 using Python to control Cisco, Juniper, and Arista eAPI network devices Leverage existing frameworks to construct high-level APIs Learn how to build virtual networks in the AWS Cloud Understand how Jenkins can be used to automatically deploy changes in your network Use PyTest and Unittest for Test-Driven Network Development Who this book is for Mastering Python Networking is for network engineers and programmers who want to use Python for networking. Basic familiarity with Python programming and networking-related concepts such as Transmission Control Protocol/Internet Protocol (TCP/IP) will be useful. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Previous edition published: 2017. - Description based on online resource; title from title page (Safari, viewed September 20, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789135992/?ar
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  • 89
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    ASP.NET Core 2 fundamentals : build cross-platform apps and dynamic web services with this server-side web application framework (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789533552 , 1789533554
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Active server pages ; Web sites ; Design ; Web site development ; Application software ; Development ; Web applications ; Electronic books ; Electronic books ; local
    Abstract: Imagine the boost in business if you can build large, rich web applications with little code and built-in Windows authentication. With this book, you can gain skills to develop real-world applications with ASP.NET Core 2. Key Features Adopts the application-centric approach to explain core concepts Covers industry-best practices to build flexible, robust applications Shows how to enhance your applications by adding more functionalities Book Description The book sets the stage with an introduction to web applications and helps you build an understanding of the tried-and-true MVC architecture. You learn all about views, from what is the Razor view engine to tagging helpers. You gain insight into what models are, how to bind them, and how to migrate database using the correct model. As you get comfortable with the world of ASP.NET, you learn about validation and routing. You also learn the advanced concepts, such as designing Rest Buy (a RESTful shopping cart application), creating entities for it, and creating EF context and migrations. By the time you are done reading the book, you will be able to optimally use ASP.NET to develop, unit test, and deploy applications like a pro. What you will learn Work with basic programming constructs using the Razor view engine Use flexibility and data compartmentalization of ViewModel Build a custom route for ASP.NET MVC applications for SEO Optimize applications with performance analysis and improvement steps Improve application performance, security, and data access to optimize the overall development process Deploy an ASP.NET MVC application in a non-Windows environment Who this book is for If you are looking to build web applications using ASP.NET Core or you want to become a pro in building web applications using the Microsoft technology, this is the ideal book for you. Prior exposure and understanding of C#, JavaScript, HTML, and CSS syntax is assumed.
    Note: Description based on online resource; title from title page (Safari, viewed October 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789538915/?ar
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  • 90
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    Raspberry Pi 3 cookbook for Python programmers : unleash the potential of Raspberry Pi 3 with over 100 recipes (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788626989 , 1788626982
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Raspberry Pi (Computer) ; Programming ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: A recipe-based guide to programming your Raspberry Pi 3 using Python About This Book Leverage the power of Raspberry Pi 3 using Python programming Create 3D games, build neural network modules, and interface with your own circuits Packed with clear, step-by-step recipes to walk you through the capabilities of Raspberry Pi Who This Book Is For This book is for anyone who wants to master the skills of Python programming using Raspberry Pi 3. Prior knowledge of Python will be an added advantage. What You Will Learn Learn to set up and run Raspberry Pi 3 Build text classifiers and perform automation using Python Predict sentiments in words and create games and graphics Detect edges and contours in images Build human face detection and recognition system Use Python to drive hardware Sense and display real-world data Build a neural network module for optical character recognition Build movie recommendations system In Detail Raspberry Pi 3 Cookbook for Python Programmers ? Third Edition begins by guiding you through setting up Raspberry Pi 3, performing tasks using Python 3.6, and introducing the first steps to interface with electronics. As you work through each chapter, you will build your skills and apply them as you progress. You will learn how to build text classifiers, predict sentiments in words, develop applications using the popular Tkinter library, and create games by controlling graphics on your screen. You will harness the power of a built in graphics processor using Pi3D to generate your own high-quality 3D graphics and environments. You will understand how to connect Raspberry Pi's hardware pins directly to control electronics, from switching on LEDs and responding to push buttons to driving motors and servos. Get to grips with monitoring sensors to gather real-life data, using it to control other devices, and viewing the results over the internet. You will apply what you have learned by creating your own Pi-Rover or Pi-Hexipod robots. You will also learn about sentiment analysis, face recognition techniques, and building neural network modules for optical character recognition. Finally, you will learn to build movie recommendations system on Raspberry Pi 3. Style and approach Written in a cookbook style, this book contains a series of recipes on various topics. It is an easy-to-follow step-by-step guide with examples of feature integration suitable for any search application.
    Note: Previous edition published: 2017. - Description based on online resource; title from title page (Safari, viewed June 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788629874/?ar
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  • 91
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    Hands-on UX design for developers : design, prototype, and implement compelling user experiences from scratch (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788624299 , 1788624297
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: User-centered system design ; Web site development ; Web sites ; Design ; Electronic books ; Electronic books ; local
    Abstract: Learn every step you need for product design and development Key Features Explore all the tools that you need to be a complete UX designer Code the product designs you've created to become a full-stack designer Build an amazing portfolio with real-world projects Book Description Designing user experience (UX) is one of the most important aspects of a project, as it has a direct effect on how customers think of your company. The process of designing a user experience is one of the most challenging yet rewarding aspects of product development. Hands-On UX Design for Developers will teach you how to create amazing user experiences for products from scratch. This book starts with helping you understand the importance of a good UX design and the role of a UX designer. It will take you through the different stages of designing a UX and the application of various principles of psychology in UX design. Next, you will learn how to conduct user research and market research, which is crucial to creating a great UX. You will also learn how to create user personas and use it for testing. This book will help you gain the ability to think like a UX designer and understand both sides of product development: design and coding. You will explore the latest tools, such as Sketch, Balsamiq, and Framer.js, to create wireframes and prototypes. The concluding chapters will take you through designing your UI, dealing with big data while designing a UX, and the fundamentals of frontend. Finally, you'll prepare your portfolio and become job ready in the UX arena. What you will learn What UX is and what a UX designer does Explore the UX Process and science of making products user-friendly Create user interfaces and learn which tools to use Understand how your design works in the real world Create UI interaction, animation, wireframes, and prototypes Design a product with users in mind Develop a personal portfolio and be well-prepared to join the UX world Who this book is for Hands-On UX/UI Design for Developers is for web designers who have knowledge of basic UX design principles.
    Note: Description based on online resource; title from title page (Safari, viewed August 29, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788626699/?ar
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  • 92
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    Hands-on enterprise automation with Python : automate common administrative and security tasks with Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788992640 , 1788992644
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Computer networks ; Management ; Automation ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Invent your own Python scripts to automate your infrastructure About This Book Make the most of Python libraries and modules to automate your infrastructure Leverage Python programming to automate server configurations and administration tasks Efficiently develop your Python skill set Who This Book Is For Hands-On Enterprise Automation with Python is for system administrators and DevOps engineers who are looking for an alternative to major automation frameworks such as Puppet and Chef. Basic programming knowledge with Python and Linux shell scripting is necessary. What You Will Learn Understand common automation modules used in Python Develop Python scripts to manage network devices Automate common Linux administration tasks with Ansible and Fabric Managing Linux processes Administrate VMware, OpenStack, and AWS instances with Python Security automation and sharing code on GitHub In Detail Hands-On Enterprise Automation with Python starts by covering the set up of a Python environment to perform automation tasks, as well as the modules, libraries, and tools you will be using. We'll explore examples of network automation tasks using simple Python programs and Ansible. Next, we will walk you through automating administration tasks with Python Fabric, where you will learn to perform server configuration and administration, along with system administration tasks such as user management, database management, and process management. As you progress through this book, you'll automate several testing services with Python scripts and perform automation tasks on virtual machines and cloud infrastructure with Python. In the concluding chapters, you will cover Python-based offensive security tools and learn how to automate your security tasks. By the end of this book, you will have mastered the skills of automating several system administration tasks with Python. Style and approach This book will follow a practical approach to help you script and automate tasks using Python. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Description based on online resource; title from title page (Safari, viewed August 8, 2018)
    URL: lizenzpflichtig
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  • 93
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    Python for offensive PenTest : a practical guide to ethical hacking and penetration testing using Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788832465 , 1788832469
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Penetration testing (Computer security) ; Application software ; Testing ; Electronic books ; Electronic books ; local
    Abstract: Your one-stop guide to using Python, creating your own hacking tools, and making the most out of resources available for this programming language About This Book Comprehensive information on building a web application penetration testing framework using Python Master web application penetration testing using the multi-paradigm programming language Python Detect vulnerabilities in a system or application by writing your own Python scripts Who This Book Is For This book is for ethical hackers; penetration testers; students preparing for OSCP, OSCE, GPEN, GXPN, and CEH; information security professionals; cybersecurity consultants; system and network security administrators; and programmers who are keen on learning all about penetration testing. What You Will Learn Code your own reverse shell (TCP and HTTP) Create your own anonymous shell by interacting with Twitter, Google Forms, and SourceForge Replicate Metasploit features and build an advanced shell Hack passwords using multiple techniques (API hooking, keyloggers, and clipboard hijacking) Exfiltrate data from your target Add encryption (AES, RSA, and XOR) to your shell to learn how cryptography is being abused by malware Discover privilege escalation on Windows with practical examples Countermeasures against most attacks In Detail Python is an easy-to-learn and cross-platform programming language that has unlimited third-party libraries. Plenty of open source hacking tools are written in Python, which can be easily integrated within your script. This book is packed with step-by-step instructions and working examples to make you a skilled penetration tester. It is divided into clear bite-sized chunks, so you can learn at your own pace and focus on the areas of most interest to you. This book will teach you how to code a reverse shell and build an anonymous shell. You will also learn how to hack passwords and perform a privilege escalation on Windows with practical examples. You will set up your own virtual hacking environment in VirtualBox, which will help you run multiple operating systems for your testing environment. By the end of this book, you will have learned how to code your own scripts and mastered ethical hacking from scratch. Style and approach This book follows a practical approach that takes a gradual learning curve, building up your knowledge about ethical hacking, right from scratch. The focus is less on theory and more on practical examples through a step-by-step approach.
    Note: Description based on online resource; title from title page (Safari, viewed May 23, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788838979/?ar
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    Django 2 web development cookbook : 100 practical recipes on building scalable Python web apps with Django 2 (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788838085 , 1788838084
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Django (Electronic resource) ; Web site development ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Create unbelievably fast, robust and secure web apps with Django Web Framework and Python 3.8 Key Features Discover solutions to a variety of web application scenarios, leveraging the power of the Django framework Understand URL routing, models, forms, templates, and RESTful services with Django 2.14 Test, deploy, and scale your web applications efficiently with Amazon Web Services Book Description Django is a framework designed to balance rapid web development with high performance. It handles high levels of user traffic and interaction, integrates with a variety of databases, and collects and processes data in real time. This book follows a task-based approach to guide you through developing with the Django 2.1 framework, starting with setting up and configuring Docker containers and a virtual environment for your project. You'll learn how to write reusable pieces of code for your models and manage database changes. You'll work with forms and views to enter and list data, applying practical examples using templates and JavaScript together for the optimum user experience. This cookbook helps you to adjust the built-in Django administration to fit your needs and sharpen security and performance to make your web applications as robust, scalable, and dependable as possible. You'll also explore integration with Django CMS, the popular content management suite. In the final chapters, you'll learn programming and debugging tricks and discover how collecting data from different sources and providing it to others in various formats can be a breeze. By the end of the book, you'll learn how to test and deploy projects to a remote dedicated server and scale your application to meet user demands. What you will learn Get started with the basic configuration necessary to start any Django project Build a database structure out of reusable model mixins Secure web applications against malicious usage and address common performance bottlenecks Integrate with, and extend, the Django CMS Construct and manage complex and deep hierarchies Import data from local sources and external web services and export it to third parties Who this book is for This book is designed for Python developers working on fast and secure web apps that can scale over time. You'll also find this book useful if you want to upgrade to latest Django framework. A background in Python 3 along with basic knowledge of the Django framework will be useful.
    Note: Previous edition published: 2016. - Description based on online resource; title from title page (Safari, viewed March 19, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788837682/?ar
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    Mastering Python design patterns : a guide to creating smart, efficient, and reusable software (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788832069 , 178883206X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Computer software ; Development ; Software patterns ; Electronic books ; Electronic books ; local
    Abstract: Exploit various design patterns to master the art of solving problems using Python Key Features Master the application design using the core design patterns and latest features of Python 3.7 Learn tricks to solve common design and architectural challenges Choose the right plan to improve your programs and increase their productivity Book Description Python is an object-oriented scripting language that is used in a wide range of categories. In software engineering, a design pattern is an elected solution for solving software design problems. Although they have been around for a while, design patterns remain one of the top topics in software engineering, and are a ready source for software developers to solve the problems they face on a regular basis. This book takes you through a variety of design patterns and explains them with real-world examples. You will get to grips with low-level details and concepts that show you how to write Python code, without focusing on common solutions as enabled in Java and C++. You'll also fnd sections on corrections, best practices, system architecture, and its designing aspects. This book will help you learn the core concepts of design patterns and the way they can be used to resolve software design problems. You'll focus on most of the Gang of Four (GoF) design patterns, which are used to solve everyday problems, and take your skills to the next level with reactive and functional patterns that help you build resilient, scalable, and robust applications. By the end of the book, you'll be able to effciently address commonly faced problems and develop applications, and also be comfortable working on scalable and maintainable projects of any size. What you will learn Explore Factory Method and Abstract Factory for object creation Clone objects using the Prototype pattern Make incompatible interfaces compatible using the Adapter pattern Secure an interface using the Proxy pattern Choose an algorithm dynamically using the Strategy pattern Keep the logic decoupled from the UI using the MVC pattern Leverage the Observer pattern to understand reactive programming Explore patterns for cloud-native, microservices, and serverless architectures Who this book is for This book is for intermediate Python developers. Prior knowledge of design patterns is not required to enjoy this book. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed October 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788837484/?ar
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    Clean code in Python : refactor your legacy code base (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788837064 , 1788837061
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Getting the most out of Python to improve your codebase Key Features Save maintenance costs by learning to fix your legacy codebase Learn the principles and techniques of refactoring Apply microservices to your legacy systems by implementing practical techniques Book Description Python is currently used in many different areas such as software construction, systems administration, and data processing. In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After reading this book, readers will understand these problems, and more importantly, how to correct them. The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into object oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform. By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code. What you will learn Set up tools to effectively work in a development environment Explore how the magic methods of Python can help us write better code Examine the traits of Python to create advanced object-oriented design Understand removal of duplicated code using decorators and descriptors Effectively refactor code with the help of unit tests Learn to implement the SOLID principles in Python Who this book is for This book will appeal to team leads, software architects and senior software engineers who would like to work on their legacy systems to save cost and improve efficiency. A strong understanding of Programming is assumed. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and registe...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed September 19, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788835831/?ar
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    Practical web design : learn the fundamentals of web design with HTML5, CSS3, Bootstrap, jQuery, and Vue.js (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788396455 , 1788396456
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Web site development ; HTML (Document markup language) ; Cascading style sheets ; Electronic books ; Electronic books ; local
    Abstract: A step by step guide for beginners to create interactive and dynamic websites from scratch. About This Book A fun-filled book with incrementing projects that would help you learn and adapt the fundamentals of web development Bring your web design to life with the help of HTML, CSS, JQuery, and learn to kick-start your future projects with Bootstrap Explore popular web development techniques such as responsive, adaptive, and material design and initiate yourself with Vue.js Who This Book Is For This book is for anyone who wants to learn about web development regardless of previous experience. It's perfect for complete beginners with zero experience; it's also great for anyone who does have some experience in a few technologies (such as HTML and CSS) but not all of them. What You Will Learn Understand the importance of web design and the basic design components Learn HTML5 and CSS3 Difference between adaptive and responsive web design Learn how to create your first website Add interaction and dynamic content to your website with JavaScript and JQuery Implement Bootstrap Framework in your project Get familiar with server-side rendering In Detail Web design is the process of creating websites. It encompasses several different aspects, including webpage layout, content production, and graphic design. This book offers you everything you need to know to build your websites. The book starts off by explaining the importance of web design and the basic design components used in website development. It'll show you insider tips to work quickly and efficiently with web technologies such as HTML5, CSS3, and JavaScript, concluding with a project on creating a static site with good layout. Once you've got that locked down, we'll get our hands dirty by diving straight into learning JavaScript and JQuery, ending with a project on creating dynamic content for your website. After getting our basic website up and running with the dynamic functionalities you'll move on to building your own responsive websites using more advanced techniques such as Bootstrap. Later you will learn smart ways to add dynamic content, and modern UI techniques such as Adaptive UI and Material Design. This will help you understand important concepts such as server-side rendering and UI components. Finally we take a look at various developer tools to ease your web development process. Style and approach This is a fun-filled book with conversational and engaging content ; with each incremen...
    Note: Description based on online resource; title from title page (Safari, viewed May 30, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788395038/?ar
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    Mastering geospatial analysis with Python : explore GIS processing and learn to work with GeoDjango, CARTOframes and MapboxGL-Jupyter (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788293815 , 1788293819
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Geographic information systems ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Explore GIS processing and learn to work with various tools and libraries in Python. About This Book Analyze and process geospatial data using Python libraries such as; Anaconda, GeoPandas Leverage new ArcGIS API to process geospatial data for the cloud. Explore various Python geospatial web and machine learning frameworks. Who This Book Is For The audience for this book includes students, developers, and geospatial professionals who need a reference book that covers GIS data management, analysis, and automation techniques with code libraries built in Python 3. What You Will Learn Manage code libraries and abstract geospatial analysis techniques using Python 3. Explore popular code libraries that perform specific tasks for geospatial analysis. Utilize code libraries for data conversion, data management, web maps, and REST API creation. Learn techniques related to processing geospatial data in the cloud. Leverage features of Python 3 with geospatial databases such as PostGIS, SQL Server, and SpatiaLite. In Detail Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API. Style and approach The book takes a practical, example-driven approach to teach you GIS analysis and automation techniques with Python 3.
    Note: Description based on online resource; title from title page (Safari, viewed June 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788293334/?ar
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    Data analysis with Python : a modern approach (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789958195 , 1789958199
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Expert insight
    Keywords: Python (Computer program language) ; Machine learning ; Artificial intelligence ; Electronic data processing ; Electronic books ; Electronic books ; local
    Abstract: Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis. Key Features Bridge your data analysis with the power of programming, complex algorithms, and AI Use Python and its extensive libraries to power your way to new levels of data insight Work with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time series Explore this modern approach across with key industry case studies and hands-on projects Book Description Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you're likely to meet in today. The first of these is an image recognition application with TensorFlow ? embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence. What you will learn A new toolset that has been carefully crafted to meet for your data analysis challenges Full and detailed case studies of the toolset across several of today's key industry contexts Become super productive with a new toolset across Python and Jupyter Notebook Look into the future of data science an...
    Note: Includes bibliographical references and index. - Description based on online resource; title from cover (Safari, viewed February 26, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789950069/?ar
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    Hands-on meta learning with Python : meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789537024 , 1789537029
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Explore a diverse set of meta-learning algorithms and techniques to enable human-like cognition for your machine learning models using various Python frameworks Key Features Understand the foundations of meta learning algorithms Explore practical examples to explore various one-shot learning algorithms with its applications in TensorFlow Master state of the art meta learning algorithms like MAML, reptile, meta SGD Book Description Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster. Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning. By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models. What you will learn Understand the basics of meta learning methods, algorithms, and types Build voice and face recognition models using a siamese network Learn the prototypical network along with its variants Build relation networks and matching networks from scratch Implement MAML and Reptile algorithms from scratch in Python Work through imitation learning and adversarial meta learning Explore task agnostic meta learning and deep meta learning Who this book is for Hands-On Meta Learning with Python is for machine learning enthusiasts, AI researchers, and data scientists who want to explore meta learning as an advanced approach for training machine learning models. Working knowledge of machine learning concepts and Python programming is necessary.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789534207/?ar
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