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  • 2015-2019  (39)
  • Safari, an O’Reilly Media Company.  (39)
  • Books on Demand GmbH
  • Verlag C.H. Beck
  • [Erscheinungsort nicht ermittelbar] : Packt Publishing  (39)
Datasource
Material
Language
Years
Year
Author, Corporation
Publisher
Keywords
  • 1
    Online Resource
    Online Resource
    Working with Legacy Systems (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838982560
    Language: English
    Pages: 1 online resource (152 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Understand the crux of legacy systems—their architecture, analysis, and security constraints Key Features Understand what legacy systems are and strategies for their maintenance Explore basic and advanced architectures of legacy systems Discover how to analyze and secure legacy systems Book Description The IT industry is constantly evolving with the introduction of new technologies. While it is important to keep up with advancements, maintaining legacy systems is equally necessary to ensure that the infrastructure of your organization functions to the best of its ability. Sound knowledge of techniques that can be used for maintaining legacy systems can help you avoid common pitfalls. The book begins with a quick overview of what a real legacy system looks like, how it works, and common issues that may be faced when trying to maintaining it. You'll then explore the architecture of a legacy system in detail and understand each of its components. As you progress, you'll discover a variety of techniques for analyzing a legacy system and how to apply them. Once you get to grips with the security constraints associated with legacy systems, you'll explore ways to secure them. Finally, you'll be able to easily make changes in legacy systems to enhance their performance. By the end of this book, you'll have developed the skills and confidence to work with legacy systems and efficiently maintain them. What you will learn Perform static and dynamic analyses of legacy systems Implement best practices to secure your legacy systems Use techniques such as data cleansing and process cleansing to stabilize your system Apply structural changes in your legacy system to make it highly available Identify and resolve common issues with legacy systems Understand a variety of tests that can help you secure and maintain legacy systems Who this book is for If you're new to working with legacy systems and want to understand how they work and how to maintain them, this book is for you.
    Note: Online resource; Title from title page (viewed June 3, 2019) , Mode of access: World Wide Web.
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  • 2
    Online Resource
    Online Resource
    Deep Learning with Real World Projects (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838985721
    Language: English
    Pages: 1 online resource (1 video file, approximately 20 hr., 49 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Novice to pro in Deep Learning with Hands-on Real-World Projects About This Video Learn to implement machine learning models in Tensor Flow and Keras Complete introduction to advance level concepts in Recurrent Neural Networks (RNN) A Practical course with multiple real-life projects in Deep learning In Detail Deep learning is an artificial intelligence function that mimics the inner workings of the human brain in processing data and creating patterns for use in decision making. Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks of interconnected nodes capable of un-supervised learning from data that is unstructured or unlabelled training data. It also enables representation of data in form of abstract features and classifies them into sub-classes which may be too complex for traditional machine learning models. One of the most common AI techniques used for processing big data is machine learning, a self-adaptive algorithm that gets increasingly better analysis and patterns with experience or with newly added data. As more and more sources of data-generation are coming into picture, the number of file formats is increasing as well. Now, designing one model to merge data from these many sources and extract meaningful insights is not possible with traditional hand-coded programs. While traditional programs build analysis with data in a linear way, the hierarchical function of deep learning systems enables machines to process data with a non-linear approach. While this may sound daunting, Deep Learning algorithms handle such tasks with ease. The scope of implementation in various sectors is just limitless.
    Note: Online resource; Title from title screen (viewed July 12, 2019) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Master Apache JMeter - From Load Testing to DevOps (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781839217647
    Language: English
    Pages: 1 online resource (468 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Learn how to get the most out of JMeter, improve the productivity of your apps, and integrate JMeter with your Agile and DevOps processes. Key Features Gain insights into preparing test environments and selecting the correct use cases to load test Learn to analyze a load test with Backend Listener, HTML Report Dashboard, and View Results Tree Explore how to integrate JMeter in the software factory Book Description Load tests help identify the maximum number of requests a software system can handle. One popular open source tool for load testing is JMeter. By leveraging the features and capabilities of JMeter, you can perform extensive load testing and fix issues in your application before they become problematic. This book is written by JMeter developers and begins by discussing the whole process, including recording a script, setting it up, and launching it, enabling you to almost immediately start load testing. You'll learn the best practices that you must follow while designing test cases. You'll also explore the different protocols offered by JMeter through various real-world examples. Finally, you'll see how to integrate JMeter into the DevOps approach and create professional reports. You'll discover ways to use the eco-system of JMeter to integrate new protocols, enrich its monitoring, and leverage its power through the use of the cloud. By the end of this book, you'll know all that's needed to perform comprehensive load testing on your applications by using all the best practices and features of JMeter. What you will learn Explore various JMeter concepts, including Timers scope and Assertions scope Discover the types of test protocols and load tests that JMeter supports Design a realistic test scenario using various tips and best practices Prepare your test environment with injectors and the system under test Learn and apply good practices when recording a script Integrate JMeter with Jenkins using Maven Who this book is for This book contains all the valuable information you need in one place and is a must for everybody who is seriously working with JMeter. It might be a little condensed for absolute beginners, but this book is the best you can find if you already have some performance testing experience and want to get further. In particular, it would be invaluable to developers who want to expand their JMeter knowledge into advanced topics or switch to JMeter from other load testing tools.
    Note: Online resource; Title from title page (viewed August 1, 2019) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 4
    Online Resource
    Online Resource
    Python Machine Learning By Example - Second Edition (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781789616729
    Language: English
    Pages: 1 online resource (382 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learn Key Features Exploit the power of Python to explore the world of data mining and data analytics Discover machine learning algorithms to solve complex challenges faced by data scientists today Use Python libraries such as TensorFlow and Keras to create smart cognitive actions for your projects Book Description The surge in interest in machine learning (ML) is due to the fact that it revolutionizes automation by learning patterns in data and using them to make predictions and decisions. If you're interested in ML, this book will serve as your entry point to ML. Python Machine Learning By Example begins with an introduction to important ML concepts and implementations using Python libraries. Each chapter of the book walks you through an industry adopted application. You'll implement ML techniques in areas such as exploratory data analysis, feature engineering, and natural language processing (NLP) in a clear and easy-to-follow way. With the help of this extended and updated edition, you'll understand how to tackle data-driven problems and implement your solutions with the powerful yet simple Python language and popular Python packages and tools such as TensorFlow, scikit-learn, gensim, and Keras. To aid your understanding of popular ML algorithms, the book covers interesting and easy-to-follow examples such as news topic modeling and classification, spam email detection, stock price forecasting, and more. By the end of the book, you'll have put together a broad picture of the ML ecosystem and will be well-versed with the best practices of applying ML techniques to make the most out of new opportunities. What you will learn Understand the important concepts in machine learning and data science Use Python to explore the world of data mining and analytics Scale up model training using varied data complexities with Apache Spark Delve deep into text and NLP using Python libraries such NLTK and gensim Select and build an ML model and evaluate and optimize its performance Implement ML algorithms from scratch in Python, TensorFlow, and scikit-learn Who this book is for If you're a machine learning aspirant, data analyst, or data engineer highly passionate about machine learning and want to begin working on ML assignments, this book is for you. Prior knowledge of Python coding is assumed and basic fami...
    Note: Online resource; Title from title page (viewed February 28, 2019) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    URL: https://learning.oreilly.com/library/view/-/9781789616729/?ar
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    Online Resource
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  • 5
    Online Resource
    Online Resource
    SQL for Data Analytics (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781789807356
    Language: English
    Pages: 1 online resource (386 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Take your first steps to become a fully qualified data analyst by learning how to explore large relational datasets Key Features Explore a variety of statistical techniques to analyze your data Integrate your SQL pipelines with other analytics technologies Perform advanced analytics such as geospatial and text analysis Book Description Understanding and finding patterns in data has become one of the most important ways to improve business decisions. If you know the basics of SQL, but don't know how to use it to gain the most effective business insights from data, this book is for you. SQL for Data Analytics helps you build the skills to move beyond basic SQL and instead learn to spot patterns and explain the logic hidden in data. You'll discover how to explore and understand data by identifying trends and unlocking deeper insights. You'll also gain experience working with different types of data in SQL, including time-series, geospatial, and text data. Finally, you'll learn how to increase your productivity with the help of profiling and automation. By the end of this book, you'll be able to use SQL in everyday business scenarios efficiently and look at data with the critical eye of an analytics professional. What you will learn Perform advanced statistical calculations using the WINDOW function Use SQL queries and subqueries to prepare data for analysis Import and export data using a text file and psql Apply special SQL clauses and functions to generate descriptive statistics Analyze special data types in SQL, including geospatial data and time data Optimize queries to improve their performance for faster results Debug queries that won't run Use SQL to summarize and identify patterns in data Who this book is for If you're a database engineer looking to transition into analytics, or a backend engineer who wants to develop a deeper understanding of production data, you will find this book useful. This book is also ideal for data scientists or business analysts who want to improve their data analytics skills using SQL. Knowledge of basic SQL and database concepts will aid in understanding the concepts covered in this book.
    Note: Online resource; Title from title page (viewed August 23, 2019) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 6
    Online Resource
    Online Resource
    Python GUI Programming - A Complete Reference Guide (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838988470
    Language: English
    Pages: 1 online resource (746 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Explore Python's GUI frameworks and create visually stunning and feature-rich applications Key Features Integrate stunning data visualizations using Tkinter Canvas and Matplotlib Understand the basics of 2D and 3D animation in GUI applications Explore PyQt's powerful features to easily design and customize your GUI applications Book Description A responsive graphical user interface (GUI) helps you interact with your application, improves user experience, and enhances the efficiency of your applications. With Python, you'll have access to elaborate GUI frameworks that you can use to build interactive GUIs that stand apart from the rest. This Learning Path begins by introducing you to Tkinter and PyQt, before guiding you through the application development process. As you expand your GUI by adding more widgets, you'll work with networks, databases, and graphical libraries that enhance its functionality. You'll also learn how to connect to external databases and network resources, test your code, and maximize performance using asynchronous programming. In later chapters, you'll understand how to use the cross-platform features of Tkinter and Qt5 to maintain compatibility across platforms. You'll be able to mimic the platform-native look and feel, and build executables for deployment across popular computing platforms. By the end of this Learning Path, you'll have the skills and confidence to design and build high-end GUI applications that can solve real-world problems. This Learning Path includes content from the following Packt products: Python GUI Programming with Tkinter by Alan D. Moore Qt5 Python GUI Programming Cookbook by B. M. Harwani What you will learn Visualize graphs in real time with Tkinter's animation capabilities Use PostgreSQL authentication to ensure data security for your application Write unit tests to avoid regression when updating code Handle different signals generated on mouse clicks using QSpinBox and sliders Employ network concepts, internet browsing, and Google Maps in UI Use graphics rendering to implement animations in your GUI Who this book is for If you're an intermediate Python programmer looking to enhance your coding skills by writing powerful GUIs in Python using PyQT and Tkinter, this is an ideal Learning Path for you. A strong understanding of the Python language is a must to grasp the concepts explained in this book.
    Note: Online resource; Title from title page (viewed June 24, 2019) , Mode of access: World Wide Web.
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  • 7
    Online Resource
    Online Resource
    Julia 1.0 Programming Complete Reference Guide (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838822248
    Language: English
    Pages: 1 online resource (466 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web Key Features Leverage Julia's high speed and efficiency to build fast, efficient applications Perform supervised and unsupervised machine learning and time series analysis Tackle problems concurrently and in a distributed environment Book Description Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There's never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You'll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You'll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you'll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you'll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: Julia 1.0 Programming - Second Edition by Ivo Balbaert Julia Programming Projects by Adrian Salceanu What you will learn Create your own types to extend the built-in type system Visualize your data in Julia with plotting packages Explore the use of built-in macros for testing and debugging Integrate Julia with other languages such as C, Python, and MATLAB Analyze and manipulate datasets using Julia and DataFrames Develop and run a web app using Julia and the HTTP package Build a recommendation system using supervised machine learning Who this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of m...
    Note: Online resource; Title from title page (viewed May 20, 2019) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 8
    Online Resource
    Online Resource
    Data Science Projects with Python (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838551025
    Language: English
    Pages: 1 online resource (374 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Gain hands-on experience with industry-standard data analysis and machine learning tools in Python Key Features Tackle data science problems by identifying the problem to be solved Illustrate patterns in data using appropriate visualizations Implement suitable machine learning algorithms to gain insights from data Book Description Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools, by applying them to realistic data problems. You will learn how to use pandas and Matplotlib to critically examine datasets with summary statistics and graphs, and extract the insights you seek to derive. You will build your knowledge as you prepare data using the scikit-learn package and feed it to machine learning algorithms such as regularized logistic regression and random forest. You'll discover how to tune algorithms to provide the most accurate predictions on new and unseen data. As you progress, you'll gain insights into the working and output of these algorithms, building your understanding of both the predictive capabilities of the models and why they make these predictions. By then end of this book, you will have the necessary skills to confidently use machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data. What you will learn Install the required packages to set up a data science coding environment Load data into a Jupyter notebook running Python Use Matplotlib to create data visualizations Fit machine learning models using scikit-learn Use lasso and ridge regression to regularize your models Compare performance between models to find the best outcomes Use k-fold cross-validation to select model hyperparameters Who this book is for If you are a data analyst, data scientist, or business analyst who wants to get started using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of Python and data analytics will help you get the most from this book. Familiarity with mathematical concepts such as algebra and basic statistics will also be useful.
    Note: Online resource; Title from title page (viewed April 30, 2019) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 9
    Online Resource
    Online Resource
    Powershell Core 6.2 Cookbook (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781789803303
    Language: English
    Pages: 1 online resource (372 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Make use of hands-on recipes for many tasks that are typically encountered in both the on-premises as well as the cloud world. Key Features A recipe-based guide to help you build effective administrative solutions Gain hands-on experience with the newly added features of PowerShell Core Manage critical business environments with professional scripting practices Book Description This book will follow a recipe-based approach and start off with an introduction to the fundamentals of PowerShell, and explaining how to install and run it through simple examples. Next, you will learn how to use PowerShell to access and manipulate data and how to work with different streams as well. You will also explore the object model which will help with regard to PowerShell function deployment. Going forward, you will get familiar with the pipeline in its different use cases. The next set of chapters will deal with the different ways of accessing data in PowerShell. You will also learn to automate various tasks in Windows and Linux using PowerShell Core, as well as explore Windows Server. Later, you will be introduced to Remoting in PowerShell Core and Just Enough Administration concept. The last set of chapters will help you understand the management of a private and public cloud with PowerShell Core. You will also learn how to access web services and explore the high-performance scripting methods. By the end of this book, you will gain the skills to manage complex tasks effectively along with increasing the performance of your environment. What you will learn Leverage cross-platform interaction with systems Make use of the PowerShell recipes for frequent tasks Get a better understanding of the inner workings of PowerShell Understand the compatibility of built-in Windows modules with PowerShell Core Learn best practices associated with PowerShell scripting Avoid common pitfalls and mistakes Who this book is for This book will be for windows administrators who want to enhance their PowerShell scripting skills to the next level. System administrators wanting to automate common to complex tasks with PowerShell scripts would benefit from this book. Prior understanding on PowerShell would be necessary. 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 h...
    Note: Online resource; Title from title page (viewed April 19, 2019) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 10
    Online Resource
    Online Resource
    Applied Supervised Learning with R (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838556334
    Language: English
    Pages: 1 online resource (502 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Learn the ropes of supervised machine learning with R by studying popular real-world use cases, and understand how it drives object detection in driverless cars, customer churn, and loan default prediction. Key Features Study supervised learning algorithms by using real-world datasets Fine tune optimal parameters with hyperparameter optimization Select the best algorithm using the model evaluation framework Book Description R provides excellent visualization features that are essential for exploring data before using it in automated learning. Applied Supervised Learning with R helps you cover the complete process of employing R to develop applications using supervised machine learning algorithms for your business needs. The book starts by helping you develop your analytical thinking to create a problem statement using business inputs and domain research. You will then learn different evaluation metrics that compare various algorithms, and later progress to using these metrics to select the best algorithm for your problem. After finalizing the algorithm you want to use, you will study the hyperparameter optimization technique to fine-tune your set of optimal parameters. The book demonstrates how you can add different regularization terms to avoid overfitting your model. By the end of this book, you will have the advanced skills you need for modeling a supervised machine learning algorithm that precisely fulfills your business needs. What you will learn Develop analytical thinking to precisely identify a business problem Wrangle data with dplyr, tidyr, and reshape2 Visualize data with ggplot2 Validate your supervised machine learning model using k-fold Optimize hyperparameters with grid and random search, and Bayesian optimization Deploy your model on Amazon Web Services (AWS) Lambda with plumber Improve your model's performance with feature selection and dimensionality reduction Who this book is for This book is specially designed for beginner and intermediate-level data analysts, data scientists, and data engineers who want to explore different methods of supervised machine learning and its use cases. Some background in statistics, probability, calculus, linear algebra, and programming will help you thoroughly understand and follow the concepts covered in this book.
    Note: Online resource; Title from title page (viewed May 31, 2019) , Mode of access: World Wide Web.
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  • 11
    Online Resource
    Online Resource
    Applied Supervised Learning with Python (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781789954920
    Language: English
    Pages: 1 online resource (404 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Explore the exciting world of machine learning with the fastest growing technology in the world Key Features Understand various machine learning concepts with real-world examples Implement a supervised machine learning pipeline from data ingestion to validation Gain insights into how you can use machine learning in everyday life Book Description Machine learning—the ability of a machine to give right answers based on input data—has revolutionized the way we do business. Applied Supervised Learning with Python provides a rich understanding of how you can apply machine learning techniques in your data science projects using Python. You'll explore Jupyter Notebooks, the technology used commonly in academic and commercial circles with in-line code running support. With the help of fun examples, you'll gain experience working on the Python machine learning toolkit—from performing basic data cleaning and processing to working with a range of regression and classification algorithms. Once you've grasped the basics, you'll learn how to build and train your own models using advanced techniques such as decision trees, ensemble modeling, validation, and error metrics. You'll also learn data visualization techniques using powerful Python libraries such as Matplotlib and Seaborn. This book also covers ensemble modeling and random forest classifiers along with other methods for combining results from multiple models, and concludes by delving into cross-validation to test your algorithm and check how well the model works on unseen data. By the end of this book, you'll be equipped to not only work with machine learning algorithms, but also be able to create some of your own! What you will learn Understand the concept of supervised learning and its applications Implement common supervised learning algorithms using machine learning Python libraries Validate models using the k-fold technique Build your models with decision trees to get results effortlessly Use ensemble modeling techniques to improve the performance of your model Apply a variety of metrics to compare machine learning models Who this book is for Applied Supervised Learning with Python is for you if you want to gain a solid understanding of machine learning using Python. It'll help if you to have some experience in any functional or object-oriented language and a basic understanding of Python libraries and expressions, such as arrays and dictionaries.
    Note: Online resource; Title from title page (viewed April 27, 2019) , Mode of access: World Wide Web.
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  • 12
    Online Resource
    Online Resource
    The Complete Rust Programming Reference Guide (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838828103
    Language: English
    Pages: 1 online resource (698 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Design and implement professional-level programs by leveraging modern data structures and algorithms in Rust Key Features Improve your productivity by writing more simple and easy code in Rust Discover the functional and reactive implementations of traditional data structures Delve into new domains of Rust, including WebAssembly, networking, and command-line tools Book Description Rust is a powerful language with a rare combination of safety, speed, and zero-cost abstractions. This Learning Path is filled with clear and simple explanations of its features along with real-world examples, demonstrating how you can build robust, scalable, and reliable programs. You'll get started with an introduction to Rust data structures, algorithms, and essential language constructs. Next, you will understand how to store data using linked lists, arrays, stacks, and queues. You'll also learn to implement sorting and searching algorithms, such as Brute Force algorithms, Greedy algorithms, Dynamic Programming, and Backtracking. As you progress, you'll pick up on using Rust for systems programming, network programming, and the web. You'll then move on to discover a variety of techniques, right from writing memory-safe code, to building idiomatic Rust libraries, and even advanced macros. By the end of this Learning Path, you'll be able to implement Rust for enterprise projects, writing better tests and documentation, designing for performance, and creating idiomatic Rust code. This Learning Path includes content from the following Packt products: Mastering Rust - Second Edition by Rahul Sharma and Vesa Kaihlavirta Hands-On Data Structures and Algorithms with Rust by Claus Matzinger What you will learn Design and implement complex data structures in Rust Create and use well-tested and reusable components with Rust Understand the basics of multithreaded programming and advanced algorithm design Explore application profiling based on benchmarking and testing Study and apply best practices and strategies in error handling Create efficient web applications with the Actix-web framework Use Diesel for type-safe database interactions in your web application Who this book is for If you are already familiar with an imperative language and now want to progress from being a beginner to an intermediate-level Rust programmer, this Learning Path is for you. Developers who are already familiar with Rust and want to delve deeper into the essential data structures and algorithms i...
    Note: Online resource; Title from title page (viewed May 22, 2019) , Mode of access: World Wide Web.
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  • 13
    Online Resource
    Online Resource
    The Complete Metasploit Guide (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838822477
    Language: English
    Pages: 1 online resource (660 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Master the Metasploit Framework and become an expert in penetration testing. Key Features Gain a thorough understanding of the Metasploit Framework Develop the skills to perform penetration testing in complex and highly secure environments Learn techniques to integrate Metasploit with the industry's leading tools Book Description Most businesses today are driven by their IT infrastructure, and the tiniest crack in this IT network can bring down the entire business. Metasploit is a pentesting network that can validate your system by performing elaborate penetration tests using the Metasploit Framework to secure your infrastructure. This Learning Path introduces you to the basic functionalities and applications of Metasploit. Throughout this book, you'll learn different techniques for programming Metasploit modules to validate services such as databases, fingerprinting, and scanning. You'll get to grips with post exploitation and write quick scripts to gather information from exploited systems. As you progress, you'll delve into real-world scenarios where performing penetration tests are a challenge. With the help of these case studies, you'll explore client-side attacks using Metasploit and a variety of scripts built on the Metasploit Framework. By the end of this Learning Path, you'll have the skills required to identify system vulnerabilities by using thorough testing. This Learning Path includes content from the following Packt products: Metasploit for Beginners by Sagar Rahalkar Mastering Metasploit - Third Edition by Nipun Jaswal What you will learn Develop advanced and sophisticated auxiliary modules Port exploits from Perl, Python, and many other programming languages Bypass modern protections such as antivirus and IDS with Metasploit Script attacks in Armitage using the Cortana scripting language Customize Metasploit modules to modify existing exploits Explore the steps involved in post-exploitation on Android and mobile platforms Who this book is for This Learning Path is ideal for security professionals, web programmers, and pentesters who want to master vulnerability exploitation and get the most of the Metasploit Framework. Basic knowledge of Ruby programming and Cortana scripting language is required.
    Note: Online resource; Title from title page (viewed June 25, 2019) , Mode of access: World Wide Web.
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  • 14
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    Improving Your Splunk Skills (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838981747
    Language: English
    Pages: 1 online resource (680 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Transform machine-generated data into valuable business insights using the powers of Splunk Key Features Explore the all-new machine learning toolkit in Splunk 7.x Tackle any problems related to searching and analyzing your data with Splunk Get the latest information and business insights on Splunk 7.x Book Description Splunk makes it easy for you to take control of your data and drive your business with the cutting edge of operational intelligence and business analytics. Through this Learning Path, you'll implement new services and utilize them to quickly and efficiently process machine-generated big data. You'll begin with an introduction to the new features, improvements, and offerings of Splunk 7. You'll learn to efficiently use wildcards and modify your search to make it faster. You'll learn how to enhance your applications by using XML dashboards and configuring and extending Splunk. You'll also find step-by-step demonstrations that'll walk you through building an operational intelligence application. As you progress, you'll explore data models and pivots to extend your intelligence capabilities. By the end of this Learning Path, you'll have the skills and confidence to implement various Splunk services in your projects. This Learning Path includes content from the following Packt products: Implementing Splunk 7 - Third Edition by James Miller Splunk Operational Intelligence Cookbook - Third Edition by Paul R Johnson, Josh Diakun, et al What you will learn Master the new offerings in Splunk: Splunk Cloud and the Machine Learning Toolkit Create efficient and effective searches Master the use of Splunk tables, charts, and graph enhancements Use Splunk data models and pivots with faster data model acceleration Master all aspects of Splunk XML dashboards with hands-on applications Apply ML algorithms for forecasting and anomaly detection Integrate advanced JavaScript charts and leverage Splunk's API Who this book is for This Learning Path is for data analysts, business analysts, and IT administrators who want to leverage the Splunk enterprise platform as a valuable operational intelligence tool. Existing Splunk users who want to upgrade and get up and running with Splunk 7.x will also find this book useful. Some knowledge of Splunk services will help you get the most out of this Learning Path.
    Note: Online resource; Title from title page (viewed August 22, 2019) , Mode of access: World Wide Web.
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  • 15
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    Introduction to DevOps with Kubernetes (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781789808285
    Language: English
    Pages: 1 online resource (374 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Become familiar with Kubernetes and explore techniques to manage your containerized workloads and services Key Features Learn everything from creating a cluster to monitoring applications in Kubernetes Understand and develop DevOps primitives using Kubernetes Use Kubernetes to solve challenging real-life DevOps problems Book Description Kubernetes and DevOps are the two pillars that can keep your business at the top by ensuring high performance of your IT infrastructure. Introduction to DevOps with Kubernetes will help you develop the skills you need to improve your DevOps with the power of Kubernetes. The book begins with an overview of Kubernetes primitives and DevOps concepts. You'll understand how Kubernetes can assist you with overcoming a wide range of real-world operation challenges. You will get to grips with creating and upgrading a cluster, and then learn how to deploy, update, and scale an application on Kubernetes. As you advance through the chapters, you'll be able to monitor an application by setting up a pod failure alert on Prometheus. The book will also guide you in configuring Alertmanager to send alerts to the Slack channel and trace down a problem on the application using kubectl commands. By the end of this book, you'll be able to manage the lifecycle of simple to complex applications on Kubernetes with confidence. What you will learn Create and manage Kubernetes clusters in on-premise systems and cloud Exercise various DevOps practices using Kubernetes Explore configuration, secret, and storage management, and exercise these on Kubernetes Perform different update techniques and apply them on Kubernetes Use the built-in scaling feature in Kubernetes to scale your applications up and down Use various troubleshooting techniques and have a monitoring system installed on Kubernetes Who this book is for If you are a developer who wants to learn how to apply DevOps patterns using Kubernetes, then this book is for you. Familiarity with Kubernetes will be useful, but not essential.
    Note: Online resource; Title from title page (viewed May 22, 2019) , Mode of access: World Wide Web.
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  • 16
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    Hands-On Microservices with Kubernetes (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781789805468
    Language: English
    Pages: 1 online resource (502 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Enhance your skills in building scalable infrastructure for your cloud-based applications Key Features Learn to design a scalable architecture by building continuous integration (CI) pipelines with Kubernetes Get an in-depth understanding of role-based access control (RBAC), continuous deployment (CD), and observability Monitor a Kubernetes cluster with Prometheus and Grafana Book Description Kubernetes is among the most popular open source platforms for automating the deployment, scaling, and operations of application containers across clusters of hosts, providing a container-centric infrastructure. Hands-On Microservices with Kubernetes starts by providing you with in-depth insights into the synergy between Kubernetes and microservices. You will learn how to use Delinkcious, which will serve as a live lab throughout the book to help you understand microservices and Kubernetes concepts in the context of a real-world application. Next, you will get up to speed with setting up a CI/CD pipeline and configuring microservices using Kubernetes ConfigMaps. As you cover later chapters, you will gain hands-on experience in securing microservices and implementing REST, gRPC APIs, and a Delinkcious data store. In addition to this, you’ll explore the Nuclio project, run a serverless task on Kubernetes, and manage and implement data-intensive tests. Toward the concluding chapters, you’ll deploy microservices on Kubernetes and learn to maintain a well-monitored system. Finally, you’ll discover the importance of service meshes and how to incorporate Istio into the Delinkcious cluster. By the end of this book, you’ll have gained the skills you need to implement microservices on Kubernetes with the help of effective tools and best practices. What you will learn Understand the synergy between Kubernetes and microservices Create a complete CI/CD pipeline for your microservices on Kubernetes Develop microservices on Kubernetes with the Go kit framework using best practices Manage and monitor your system using Kubernetes and open source tools Expose your services through REST and gRPC APIs Implement and deploy serverless functions as a service Externalize authentication, authorization, and traffic shaping using a service mesh Run a Kubernetes cluster in the cloud on Google Kubernetes Engine Who this book is for This book is for developers, DevOps engineers, or anyone who wants to develop large-scale microservice-based systems on top of Kubernetes. If you are look...
    Note: Online resource; Title from title page (viewed July 5, 2019) , Mode of access: World Wide Web.
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  • 17
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    Programming Microsoft Dynamics 365 Business Central - Sixth Edition (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781789137798
    Language: English
    Pages: 1 online resource (536 pages)
    Edition: 6th edition
    Keywords: Electronic books
    Abstract: Explore the fundamentals of Dynamics 365 Business Central and the Visual Studio Code development environment with the help of useful examples and case studies Key Features Tailor your applications to best suit the needs of your business Explore the latest features of Business Central with examples curated by industry experts Integrate Business Central features in your applications with this comprehensive guide Book Description Microsoft Dynamics 365 Business Central is a full ERP business solution suite with a robust set of development tools to support customization and enhancement. These tools can be used to tailor Business Central's in-built applications to support complete management functions for finance, supply chain, manufacturing, and operations. Using a case study approach, this book will introduce you to Dynamics 365 Business Central and Visual Studio Code development tools to help you become a productive Business Central developer. You'll also learn how to evaluate a product's development capabilities and manage Business Central-based development and implementation. You'll explore application structure, the construction of and uses for each object type, and how it all fits together to build apps that meet special business requirements. By the end of this book, you'll understand how to design and develop high-quality software using the Visual Studio Code development environment, the AL language paired with the improved editor, patterns, and features. What you will learn Programming using the AL language in the Visual Studio Code development environment Explore functional design and development using AL How to build interactive pages and learn how to extract data for users How to use best practices to design and develop modifications for new functionality integrated with the standard Business Central software Become familiar with deploying the broad range of components available in a Business Central system Create robust, viable systems to address specific business requirements Who this book is for If you want to learn about Dynamics 365 Business Central's powerful and extensive built-in development capabilities, this is the book for you. ERP consultants and managers of Business Central development will also find this book helpful. Although you aren't expected to have worked with Dynamics Business Central, basic understanding of programming and familiarity with business application software will help you understand the concepts covered...
    Note: Online resource; Title from title page (viewed April 30, 2019) , Mode of access: World Wide Web.
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  • 18
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    The Complete Kubernetes Guide (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838647346
    Language: English
    Pages: 1 online resource (628 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Design, deploy, and manage large-scale containers using Kubernetes Key Features Gain insight into the latest features of Kubernetes, including Prometheus and API aggregation Discover ways to keep your clusters always available, scalable, and up-to-date Master the skills of designing and deploying large clusters on various cloud platforms Book Description If you are running a number of containers and want to be able to automate the way they're managed, it can be helpful to have Kubernetes at your disposal. This Learning Path guides you through core Kubernetes constructs, such as pods, services, replica sets, replication controllers, and labels. You'll get started by learning how to integrate your build pipeline and deployments in a Kubernetes cluster. As you cover more chapters in the Learning Path, you'll get up to speed with orchestrating updates behind the scenes, avoiding downtime on your cluster, and dealing with underlying cloud provider instability in your cluster. With the help of real-world use cases, you'll also explore options for network configuration, and understand how to set up, operate, and troubleshoot various Kubernetes networking plugins. In addition to this, you'll gain insights into custom resource development and utilization in automation and maintenance workflows. By the end of this Learning Path, you'll have the expertise you need to progress from an intermediate to an advanced level of understanding Kubernetes. This Learning Path includes content from the following Packt products: Getting Started with Kubernetes - Third Edition by Jonathan Baier and Jesse White Mastering Kubernetes - Second Edition by Gigi Sayfan What you will learn Download, install, and configure the Kubernetes code base Create and configure custom Kubernetes resources Use third-party resources in your automation workflows Deliver applications as standard packages Set up and access monitoring and logging for Kubernetes clusters Set up external access to applications running in the cluster Manage and scale Kubernetes with hosted platforms on Amazon Web Services (AWS), Azure, and Google Cloud Platform (GCP) Run multiple clusters and manage them from a single control plane Who this book is for If you are a developer or a system administrator with an intermediate understanding of Kubernetes and want to master its advanced features, then this book is for you. Basic knowledge of networking is required to easily understand the concepts explained.
    Note: Online resource; Title from title page (viewed May 20, 2019) , Mode of access: World Wide Web.
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  • 19
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    Practical Machine Learning with R (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838550134
    Language: English
    Pages: 1 online resource (416 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Understand how machine learning works and get hands-on experience of using R to build algorithms that can solve various real-world problems Key Features Gain a comprehensive overview of different machine learning techniques Explore various methods for selecting a particular algorithm Implement a machine learning project from problem definition through to the final model Book Description With huge amounts of data being generated every moment, businesses need applications that apply complex mathematical calculations to data repeatedly and at speed. With machine learning techniques and R, you can easily develop these kinds of applications in an efficient way. Practical Machine Learning with R begins by helping you grasp the basics of machine learning methods, while also highlighting how and why they work. You will understand how to get these algorithms to work in practice, rather than focusing on mathematical derivations. As you progress from one chapter to another, you will gain hands-on experience of building a machine learning solution in R. Next, using R packages such as rpart, random forest, and multiple imputation by chained equations (MICE), you will learn to implement algorithms including neural net classifier, decision trees, and linear and non-linear regression. As you progress through the book, you'll delve into various machine learning techniques for both supervised and unsupervised learning approaches. In addition to this, you'll gain insights into partitioning the datasets and mechanisms to evaluate the results from each model and be able to compare them. By the end of this book, you will have gained expertise in solving your business problems, starting by forming a good problem statement, selecting the most appropriate model to solve your problem, and then ensuring that you do not overtrain it. What you will learn Define a problem that can be solved by training a machine learning model Obtain, verify and clean data before transforming it into the correct format for use Perform exploratory analysis and extract features from data Build models for neural net, linear and non-linear regression, classification, and clustering Evaluate the performance of a model with the right metrics Implement a classification problem using the neural net package Employ a decision tree using the random forest library Who this book is for If you are a data analyst, data scientist, or a business analyst who wants to understand the process of machine learni...
    Note: Online resource; Title from title page (viewed August 30, 2019) , Mode of access: World Wide Web.
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  • 20
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    Principles of Strategic Data Science (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838985295
    Language: English
    Pages: 1 online resource (104 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Take the strategic and systematic approach to analyze data to solve business problems Key Features Gain detailed information about the theory of data science Augment your coding knowledge with practical data science techniques for efficient data analysis Learn practical ways to strategically and systematically use data Book Description Principles of Strategic Data Science is created to help you join the dots between mathematics, programming, and business analysis. With a unique approach that bridges the gap between mathematics and computer science, this book takes you through the entire data science pipeline. The book begins by explaining what data science is and how organizations can use it to revolutionize the way they use their data. It then discusses the criteria for the soundness of data products and how to best visualize information. As you progress, you'll discover the strategic aspects of data science by learning the five-phase framework that enables you to enhance the value you extract from data. The final chapter of the book discusses the role of a data science manager in helping an organization take the data-driven approach. By the end of this book, you'll have a good understanding of data science and how it can enable you to extract value from your data. What you will learn Get familiar with the five most important steps of data science Use the Conway diagram to visualize the technical skills of the data science team Understand the limitations of data science from a mathematical and ethical perspective Get a quick overview of machine learning Gain insight into the purpose of using data science in your work Understand the role of data science managers and their expectations Who this book is for This book is ideal for data scientists and data analysts who are looking for a practical guide to strategically and systematically use data. This book is also useful for those who want to understand in detail what is data science and how can an organization take the data-driven approach. Prior programming knowledge of Python and R is assumed.
    Note: Online resource; Title from title page (viewed June 3, 2019) , Mode of access: World Wide Web.
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  • 21
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    Mastering Palo Alto Networks (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838550448
    Language: English
    Pages: 1 online resource (1 video file, approximately 8 hr., 51 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Dominate and take control of all the features that Palo Alto firewalls can offer to protect and secure your network About This Video Easily navigate Palo Alto’s web user interface Understand complex settings and scenarios easily Granularly monitor and take action on your network Application Command Center(ACC) This training session covers current and new features in PAN-OS 8.0.x – 8.1.x. Review and helps you understand what has changed in PAN-OS 8 In Detail Network security is not a choice; it’s a must! Palo Alto Networks is one of the top firewall platform choices when it comes to protecting and securing all your critical on-premise and cloud infrastructures. That said, it’s highly probable that you—as a Network Security Engineer—is or will be managing or deploying one in your own or your customers’ environments. This training guide will help you fully understand what tools, features, and options your Palo Alto firewalls can offer to protect and enhance visibility in your network traffic. It has been developed by someone who understands that learning every possible aspect of a technology platform can consume precious time. Why is this course perfect for you? It will get you from zero to hero in no time, so you can take full advantage of all of the features that the Palo Alto firewall platform has to offer. From initial policy configurations to configuring Nat and security rules to performing Active-Active highly available clusters, you’ll learn all there is required to set it up like a pro! After completing this training guide, you’ll feel confident that you can take full advantage of all of the features of Palo Alto firewall and most importantly, keep the bad guys out of your network.
    Note: Online resource; Title from title screen (viewed May 31, 2019) , Mode of access: World Wide Web.
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  • 22
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    Modern Programming : Object Oriented Programming and Best Practices (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838986186
    Language: English
    Pages: 1 online resource (266 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Discover the untapped features of object-oriented programming and use it with other software tools to code fast, efficient applications. Key Features Explore the complexities of object-oriented programming (OOP) Discover what OOP can do for you Learn to use the key tools and software engineering practices to support your own programming needs Book Description Your experience and knowledge always influence the approach you take and the tools you use to write your programs. With a sound understanding of how to approach your goal and what software paradigms to use, you can create high-performing applications quickly and efficiently. In this two-part book, you'll discover the untapped features of object-oriented programming and use it with other software tools to code fast and efficient applications. The first part of the book begins with a discussion on how OOP is used today and moves on to analyze the ideas and problems that OOP doesn't address. It continues by deconstructing the complexity of OOP, showing you its fundamentally simple core. You'll see that, by using the distinctive elements of OOP, you can learn to build your applications more easily. The next part of this book talks about acquiring the skills to become a better programmer. You'll get an overview of how various tools, such as version control and build management, help make your life easier. This book also discusses the pros and cons of other programming paradigms, such as aspect-oriented programming and functional programming, and helps to select the correct approach for your projects. It ends by talking about the philosophy behind designing software and what it means to be a "good" developer. By the end of this two-part book, you will have learned that OOP is not always complex, and you will know how you can evolve into a better programmer by learning about ethics, teamwork, and documentation. What you will learn Untangle the complexity of object-oriented programming by breaking it down to its essential building blocks Realize the full potential of OOP to design efficient, maintainable programs Utilize coding best practices, including TDD, pair programming and code reviews, to improve your work Use tools, such as source control and IDEs, to work more efficiently Learn how to most productively work with other developers Build your own software development philosophy Who this book is for This book is ideal for programmers who want to understand the philosophy behind creating soft...
    Note: Online resource; Title from title page (viewed June 28, 2019) , Mode of access: World Wide Web.
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    Mastering SQL Server 2017 (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838983208
    Language: English
    Pages: 1 online resource (696 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Leverage the power of SQL Server 2017 Integration Services to build data integration solutions with ease Key Features Work with temporal tables to access information stored in a table at any time Get familiar with the latest features in SQL Server 2017 Integration Services Program and extend your packages to enhance their functionality Book Description Microsoft SQL Server 2017 uses the power of R and Python for machine learning and containerization-based deployment on Windows and Linux. By learning how to use the features of SQL Server 2017 effectively, you can build scalable apps and easily perform data integration and transformation. You'll start by brushing up on the features of SQL Server 2017. This Learning Path will then demonstrate how you can use Query Store, columnstore indexes, and In-Memory OLTP in your apps. You'll also learn to integrate Python code in SQL Server and graph database implementations for development and testing. Next, you'll get up to speed with designing and building SQL Server Integration Services (SSIS) data warehouse packages using SQL server data tools. Toward the concluding chapters, you'll discover how to develop SSIS packages designed to maintain a data warehouse using the data flow and other control flow tasks. By the end of this Learning Path, you'll be equipped with the skills you need to design efficient, high-performance database applications with confidence. This Learning Path includes content from the following Packt books: SQL Server 2017 Developer's Guide by Milos Radivojevic, Dejan Sarka, et. al SQL Server 2017 Integration Services Cookbook by Christian Cote, Dejan Sarka, et. al What you will learn Use columnstore indexes to make storage and performance improvements Extend database design solutions using temporal tables Exchange JSON data between applications and SQL Server Migrate historical data to Microsoft Azure by using Stretch Database Design the architecture of a modern Extract, Transform, and Load (ETL) solution Implement ETL solutions using Integration Services for both on-premise and Azure data Who this book is for This Learning Path is for database developers and solution architects looking to develop ETL solutions with SSIS, and explore the new features in SSIS 2017. Advanced analysis practitioners, business intelligence developers, and database consultants dealing with performance tuning will also find this book useful. Basic understanding of database concepts and T-SQL is required to ...
    Note: Online resource; Title from title page (viewed August 22, 2019) , Mode of access: World Wide Web.
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    Artificial Vision and Language Processing for Robotics (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838552268
    Language: English
    Pages: 1 online resource (356 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Create end-to-end systems that can power robots with artificial vision and deep learning techniques Key Features Study ROS, the main development framework for robotics, in detail Learn all about convolutional neural networks, recurrent neural networks, and robotics Create a chatbot to interact with the robot Book Description Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment. What you will learn Explore the ROS and build a basic robotic system Understand the architecture of neural networks Identify conversation intents with NLP techniques Learn and use the embedding with Word2Vec and GloVe Build a basic CNN and improve it using generative models Use deep learning to implement artificial intelligence(AI)and object recognition Develop a simple object recognition system using CNNs Integrate AI with ROS to enable your robot to recognize objects Who this book is for Artificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus.
    Note: Online resource; Title from title page (viewed April 30, 2019) , Mode of access: World Wide Web.
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  • 25
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    Associations and Correlations (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838980412
    Language: English
    Pages: 1 online resource (134 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Discover the story of your data using the essential elements of associations and correlations Key Features Get a comprehensive introduction to associations and correlations Explore multivariate analysis, understand its limitations, and discover the assumptions on which it's based Gain insights into the various ways of preparing your data for analysis and visualization Book Description Associations and correlations are ways of describing how a pair of variables change together as a result of their connection. By knowing the various available techniques, you can easily and accurately discover and visualize the relationships in your data. This book begins by showing you how to classify your data into the four distinct types that you are likely to have in your dataset. Then, with easy-to-understand examples, you'll learn when to use the various univariate and multivariate statistical tests. You'll also discover what to do when your univariate and multivariate results do not match. As the book progresses, it describes why univariate and multivariate techniques should be used as a tag team, and also introduces you to the techniques of visualizing the story of your data. By the end of the book, you'll know exactly how to select the most appropriate univariate and multivariate tests, and be able to use a single strategic framework to discover the true story of your data. What you will learn Identify a dataset that's fit for analysis using its basic features Understand the importance of associations and correlations Use multivariate and univariate statistical tests to confirm relationships Classify data as qualitative or quantitative and then into the four subtypes Build a visual representation of all the relationships in the dataset Automate associations and correlations with CorrelViz Who this book is for This is a book for beginners – if you're a novice data analyst or data scientist, then this is a great place to start. Experienced data analysts might also find value in this title, as it will recap the basics and strengthen your understanding of key concepts. This book focuses on introducing the essential elements of association and correlation analysis.
    Note: Online resource; Title from title page (viewed June 28, 2019) , Mode of access: World Wide Web.
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    Applied Deep Learning with Keras (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838555078
    Language: English
    Pages: 1 online resource (412 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Take your neural networks to a whole new level with the simplicity and modularity of Keras, the most commonly used high-level neural networks API. Key Features Solve complex machine learning problems with precision Evaluate, tweak, and improve your deep learning models and solutions Use different types of neural networks to solve real-world problems Book Description Though designing neural networks is a sought-after skill, it is not easy to master. With Keras, you can apply complex machine learning algorithms with minimum code. Applied Deep Learning with Keras starts by taking you through the basics of machine learning and Python all the way to gaining an in-depth understanding of applying Keras to develop efficient deep learning solutions. To help you grasp the difference between machine and deep learning, the book guides you on how to build a logistic regression model, first with scikit-learn and then with Keras. You will delve into Keras and its many models by creating prediction models for various real-world scenarios, such as disease prediction and customer churning. You'll gain knowledge on how to evaluate, optimize, and improve your models to achieve maximum information. Next, you'll learn to evaluate your model by cross-validating it using Keras Wrapper and scikit-learn. Following this, you'll proceed to understand how to apply L1, L2, and dropout regularization techniques to improve the accuracy of your model. To help maintain accuracy, you'll get to grips with applying techniques including null accuracy, precision, and AUC-ROC score techniques for fine tuning your model. By the end of this book, you will have the skills you need to use Keras when building high-level deep neural networks. What you will learn Understand the difference between single-layer and multi-layer neural network models Use Keras to build simple logistic regression models, deep neural networks, recurrent neural networks, and convolutional neural networks Apply L1, L2, and dropout regularization to improve the accuracy of your model Implement cross-validate using Keras wrappers with scikit-learn Understand the limitations of model accuracy Who this book is for If you have basic knowledge of data science and machine learning and want to develop your skills and learn about artificial neural networks and deep learning, you will find this book useful. Prior experience of Python programming and experience with statistics and logistic regression will help you get the mo...
    Note: Online resource; Title from title page (viewed April 24, 2019) , Mode of access: World Wide Web.
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    Agile Technical Practices Distilled (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838980849
    Language: English
    Pages: 1 online resource (442 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Delve deep into the various technical practices, principles, and values of Agile. Key Features Discover the essence of Agile software development and the key principles of software design Explore the fundamental practices of Agile working, including test-driven development (TDD), refactoring, pair programming, and continuous integration Learn and apply the four elements of simple design Book Description The number of popular technical practices has grown exponentially in the last few years. Learning the common fundamental software development practices can help you become a better programmer. This book uses the term Agile as a wide umbrella and covers Agile principles and practices, as well as most methodologies associated with it. You'll begin by discovering how driver-navigator, chess clock, and other techniques used in the pair programming approach introduce discipline while writing code. You'll then learn to safely change the design of your code using refactoring. While learning these techniques, you'll also explore various best practices to write efficient tests. The concluding chapters of the book delve deep into the SOLID principles - the five design principles that you can use to make your software more understandable, flexible and maintainable. By the end of the book, you will have discovered new ideas for improving your software design skills, the relationship within your team, and the way your business works. What you will learn Learn the red, green, refactor cycle of classic TDD and practice the best habits such as the rule of 3, triangulation, object calisthenics, and more Refactor using parallel change and improve legacy code with characterization tests, approval tests, and Golden Master Use code smells as feedback to improve your design Learn the double cycle of ATDD and the outside-in mindset using mocks and stubs correctly in your tests Understand how Coupling, Cohesion, Connascence, SOLID principles, and code smells are all related Improve the understanding of your business domain using BDD and other principles for "doing the right thing, not only the thing right" Who this book is for This book is designed for software developers looking to improve their technical practices. Software coaches may also find it helpful as a teaching reference manual. This is not a beginner's book on how to program. You must be comfortable with at least one programming language and must be able to write unit tests using any unit testing framework.
    Note: Online resource; Title from title page (viewed June 28, 2019) , Mode of access: World Wide Web.
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    The New Engineering Game (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781839214943
    Language: English
    Pages: 1 online resource (130 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Adapt to a world of digitalization and get ready to become a successful player in the new engineering game Key Features Discover what the fourth industrial revolution is all about Explore the new engineering game through the context of globalization, craftsmanship, and interdisciplinary engineering Develop strategies to improve the engineering of products with functional architecture, lean systems engineering, and more Book Description Organizations today face an increasingly complex and dynamic environment, whatever their market. This change requires new systems that are built on the foundation of a new kind of engineering and thinking. The New Engineering Game closes the gap between high-level reflections about digitalization and daily engineering methods and tools. The book begins by describing the first three industrial revolutions and their consequences, and by predicting the fourth industrial revolution. Considering the fourth industrial revolution, it explains the need for a new kind of engineering. The later chapters of the book provide valuable principles, patterns, methods, and tools that engineering organizations can learn and use to succeed on the playfield of digitalization. By the end of the book, you'll have all the information you need to understand the various concepts to take your first steps towards the world of digitalization. What you will learn Deal with the challenges of Conway's Law Explore domains from different viewpoints with the Cynefin framework Use the Business Model Canvas (BMC) to view your business model in one chart Use the Business Model Navigator (BMN) to elaborate your business model Get an overview of REThink 4.0 Discover how to apply the principles of the Agile Manifesto for Software Development in your projects Who this book is for This book is for those of you who want to want to gear up for the ever-evolving and dynamic environment that has come into play with digitalization. Anyone who wants to create industry-grade applications using smart product engineering techniques will find this book useful. To grasp all that has been explained in this book, all you need is a knowledge-seeking attitude.
    Note: Online resource; Title from title page (viewed August 30, 2019) , Mode of access: World Wide Web.
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  • 29
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    Dancing with Qubits (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (516 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Explore the principles and practicalities of quantum computing Key Features Discover how quantum computing works and delve into the math behind it with this quantum computing textbook Learn how it may become the most important new computer technology of the century Explore the inner workings of quantum computing technology to quickly process complex cloud data and solve problems Book Description Quantum computing is making us change the way we think about computers. Quantum bits, a.k.a. qubits, can make it possible to solve problems that would otherwise be intractable with current computing technology. Dancing with Qubits is a quantum computing textbook that starts with an overview of why quantum computing is so different from classical computing and describes several industry use cases where it can have a major impact. From there it moves on to a fuller description of classical computing and the mathematical underpinnings necessary to understand such concepts as superposition, entanglement, and interference. Next up is circuits and algorithms, both basic and more sophisticated. It then nicely moves on to provide a survey of the physics and engineering ideas behind how quantum computing hardware is built. Finally, the book looks to the future and gives you guidance on understanding how further developments will affect you. Really understanding quantum computing requires a lot of math, and this book doesn't shy away from the necessary math concepts you'll need. Each topic is introduced and explained thoroughly, in clear English with helpful examples. What you will learn See how quantum computing works, delve into the math behind it, what makes it different, and why it is so powerful with this quantum computing textbook Discover the complex, mind-bending mechanics that underpin quantum systems Understand the necessary concepts behind classical and quantum computing Refresh and extend your grasp of essential mathematics, computing, and quantum theory Explore the main applications of quantum computing to the fields of scientific computing, AI, and elsewhere Examine a detailed overview of qubits, quantum circuits, and quantum algorithm Who this book is for Dancing with Qubits is a quantum computing textbook for those who want to deeply explore the inner workings of quantum computing. This entails some sophisticated mathematical exposition and is therefore best suited for those with a healthy interest in mathematics, physics, engineering, and comput...
    Note: Online resource; Title from title page (viewed November 28, 2019) , Mode of access: World Wide Web.
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  • 30
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    Data Statistics with Full Stack Python (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838986612
    Language: English
    Pages: 1 online resource (1 video file, approximately 14 hr., 17 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Master Data Science skills using Python and real time project and go from Beginner to Super Advance level About This Video Master complex theories, algorithms, and coding libraries in a very simple way Master Data Science in Python In Detail Want to become a good Data Scientist? Then this is a right course for you. This course was designed by IT professionals with a Master's in Mathematics and Data Science. We cover complex theories, algorithms, and coding libraries in a very simple way so they can be easily grasped by any beginner. We walk you step-by-step through the World of Data science. With every tutorial, you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science from beginner to advanced level.
    Note: Online resource; Title from title screen (viewed July 24, 2019) , Mode of access: World Wide Web.
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  • 31
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    Hands-On Infrastructure Monitoring with Prometheus (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (442 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Build Prometheus ecosystems with metric-centric visualization, alerting, and querying Key Features Integrate Prometheus with Alertmanager and Grafana for building a complete monitoring system Explore PromQL, Prometheus' functional query language, with easy-to-follow examples Learn how to deploy Prometheus components using Kubernetes and traditional instances Book Description Prometheus is an open source monitoring system. It provides a modern time series database, a robust query language, several metric visualization possibilities, and a reliable alerting solution for traditional and cloud-native infrastructure. This book covers the fundamental concepts of monitoring and explores Prometheus architecture, its data model, and how metric aggregation works. Multiple test environments are included to help explore different configuration scenarios, such as the use of various exporters and integrations. You'll delve into PromQL, supported by several examples, and then apply that knowledge to alerting and recording rules, as well as how to test them. After that, alert routing with Alertmanager and creating visualizations with Grafana is thoroughly covered. In addition, this book covers several service discovery mechanisms and even provides an example of how to create your own. Finally, you'll learn about Prometheus federation, cross-sharding aggregation, and also long-term storage with the help of Thanos. By the end of this book, you'll be able to implement and scale Prometheus as a full monitoring system on-premises, in cloud environments, in standalone instances, or using container orchestration with Kubernetes. What you will learn Grasp monitoring fundamentals and implement them using Prometheus Discover how to extract metrics from common infrastructure services Find out how to take full advantage of PromQL Design a highly available, resilient, and scalable Prometheus stack Explore the power of Kubernetes Prometheus Operator Understand concepts such as federation and cross-shard aggregation Unlock seamless global views and long-term retention in cloud-native apps with Thanos Who this book is for If you're a software developer, cloud administrator, site reliability engineer, DevOps enthusiast or system admin looking to set up a fail-safe monitoring and alerting system for sustaining infrastructure security and performance, this book is for you. Basic networking and infrastructure monitoring knowledge will help you understand the concepts covered in ...
    Note: Online resource; Title from title page (viewed May 31, 2019) , Mode of access: World Wide Web.
    URL: https://learning.oreilly.com/library/view/-/9781789612349/?ar
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  • 32
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    Deep Learning with TensorFlow 2 and Keras - Second Edition (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (646 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key Features Introduces and then uses TensorFlow 2 and Keras right from the start Teaches key machine and deep learning techniques Understand the fundamentals of deep learning and machine learning through clear explanations and extensive code samples Book Description Deep Learning with TensorFlow 2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You'll learn how to write deep learning applications in the most powerful, popular, and scalable machine learning stack available. TensorFlow is the machine learning library of choice for professional applications, while Keras offers a simple and powerful Python API for accessing TensorFlow. TensorFlow 2 provides full Keras integration, making advanced machine learning easier and more convenient than ever before. This book also introduces neural networks with TensorFlow, runs through the main applications (regression, ConvNets (CNNs), GANs, RNNs, NLP), covers two working example apps, and then dives into TF in production, TF mobile, and using TensorFlow with AutoML. What you will learn Build machine learning and deep learning systems with TensorFlow 2 and the Keras API Use Regression analysis, the most popular approach to machine learning Understand ConvNets (convolutional neural networks) and how they are essential for deep learning systems such as image classifiers Use GANs (generative adversarial networks) to create new data that fits with existing patterns Discover RNNs (recurrent neural networks) that can process sequences of input intelligently, using one part of a sequence to correctly interpret another Apply deep learning to natural human language and interpret natural language texts to produce an appropriate response Train your models on the cloud and put TF to work in real environments Explore how Google tools can automate simple ML workflows without the need for complex modeling Who this book is for This book is for Python developers and data scientists who want to build machine learning and deep learning systems with TensorFlow. Whether or not you have done machine learning before, this book gives you the theory and practice required to use Keras, TensorFlow 2, and AutoML to build machine learning systems.
    Note: Online resource; Title from title page (viewed December 27, 2019) , Mode of access: World Wide Web.
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    The Complete Self-Driving Car Course - Applied Deep Learning (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838829414
    Language: English
    Pages: 1 online resource (1 video file, approximately 17 hr., 50 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Use deep learning, Computer Vision, and machine learning techniques to build an autonomous car with Python About This Video The transition from a beginner to deep learning expert Learn through demonstrations as your instructor completes each task with you No experience required In Detail Self-driving cars have emerged to be one of the most transformative technologies. Fueled by deep learning algorithms, they are rapidly developing and creating new opportunities in the mobility sector. Deep learning jobs command some of the highest salaries in the development world. This is the first and one of the only courses that make practical use of deep learning and applies it to building a self-driving car. You’ll learn and master deep learning in this fun and exciting course with top instructor Rayan Slim. Having trained thousands of students, Rayan is a highly rated and experienced instructor who follows a learning-by-doing approach. By the end of the course, you will have built a fully functional self-driving car powered entirely by deep learning. This powerful simulation will impress even the most senior developers and ensure you have hands-on skills in neural networks that you can bring to any project or company. This course will show you how to do the following: Use Computer Vision techniques via OpenCV to identify lane lines for a self-driving car Train a perceptron-based neural network to classify between binary classes Train convolutional neural networks to identify various traffic signs Train deep neural networks to fit complex datasets Master Keras, a power neural network library written in Python Build and train a fully functional self-driving car Downloading the example code for this course: You can download the example code files for this course on GitHub at the following link: https://github.com/PacktPublishing/The-Complete-Self-Driving-Car-Course---Applied-Deep-Learning . If you require support please email: customercarepackt.com
    Note: Online resource; Title from title screen (viewed April 4, 2019) , Mode of access: World Wide Web.
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    Natural Language Processing with Real World Projects (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838980481
    Language: English
    Pages: 1 online resource (1 video file, approximately 14 hr., 56 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Become a Pro in Natural Language Processing About This Video To know how Apple Siri / Google Assistant Works To know how Machine can understand Human language Help Google find bad data from good data In Detail You will learn how machine can be trained to make sense of language humans use to interact. You will come across many NLP algorithms that teach the computational models about Lexical processing, basic syntactic processing. You will learn the mechanism Google translator uses, to understand the context of language and converts to a different language. You will build a chat-bot using an open-source tool Rasa, which is a text and voice-based conversations, understand messages, hold conversations, and connect to messaging channels and APIs. You will also learn to train the model you have created on NLU. The machine cannot be trained to understand or process data by traditional hand coded programs that rely heavily on very specific conditions. The moment there is a change in input, the hand coded program is rendered useless. So, rather than having to code possible conversations, we require a model that enables the system to make sense of context. By the end of the course you will be able to build NLP models that can summarize blocks of text to extract most important ideas, sentiment analysis to extract the sentiments from given block of text, identification of type entity extracted. All the projects included in this course are Real-World projects.
    Note: Online resource; Title from title screen (viewed July 24, 2019) , Mode of access: World Wide Web.
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  • 35
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    Mastering Microsoft Dynamics 365 Business Central (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (770 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Develop customized business management solutions with the latest features of Microsoft Dynamics 365 Business Central Key Features Learn Dynamics 365 Business Central, the next generation of Dynamics NAV Explore advanced topics for handling complex integrations such as using APIs, OData, and Azure Functions Discover best practices for developing SaaS extensions and moving existing solutions to the cloud Book Description Dynamics 365 Business Central is an all-in-one business management solution, which is easy to adopt and helps you make smarter business decisions. This book is a comprehensive guide to developing solutions with Microsoft ERP (in the cloud and also on-premises). It covers all aspects of developing extensions, right from preparing a sandbox environment to deploying a complete solution. The book starts by introducing you to the Dynamics 365 Business Central platform and the new Modern Development Environment. You'll then explore the sandbox concept, and see how to create sandboxes for development. As you advance, you’ll be able to build a complete advanced solution for Dynamics 365 Business Central with AL language and Visual Studio Code. You'll then learn how to debug and deploy the extension and write automatic testing. The book will also take you through advanced topics like integration (with Azure Functions, web services, and APIs), DevOps and CI/CD techniques, and machine learning. You'll discover how Dynamics 365 Business Central can be used with Office 365 apps. Finally, you'll analyze different ways to move existing solutions to the new development model based on extensions. By the end of this book, you'll be able to develop highly customized solutions that meet the requirements of modern businesses using Dynamics 365 Business Central. What you will learn Create a sandbox environment with Dynamics 365 Business Central Handle source control management when developing solutions Explore extension testing, debugging, and deployment Create real-world business processes using Business Central and different Azure services Integrate Business Central with external applications Apply DevOps and CI/CD to development projects Move existing solutions to the new extension-based architecture Who this book is for If you're a new developer looking to get started with Dynamics 365 Business Central, this book is for you. This book will also help experienced professionals enhance their knowledge and understanding of Dynamics 365 Business Central.
    Note: Online resource; Title from title page (viewed December 20, 2019) , Mode of access: World Wide Web.
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  • 36
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    Machine Learning with Real World Projects (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838985363
    Language: English
    Pages: 1 online resource (1 video file, approximately 29 hr., 48 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local ; Electronic videos
    Abstract: Go from Beginner to Super Advance Level in Machine Learning Algorithms using Python and Mathematical Insights About This Video Learn Machine Learning with real-world case studies Learn complex theory, algorithms and coding libraries in a very simple way In Detail Want to become a good Data Scientist? Then this is a right course for you. This course has been designed by IIT professionals who have mastered in Mathematics and Data Science. We will be covering complex theory, algorithms and coding libraries in a very simple way which can be easily grasped by any beginner as well. We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science from beginner to advance level. We have solved few Kaggle problems during this course and provided complete solutions so that students can easily compete in real world competition websites.
    Note: Online resource; Title from title screen (viewed July 24, 2019) , Mode of access: World Wide Web.
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  • 37
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    React Material-UI Cookbook (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (534 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Develop modern-day applications by implementing Material Design principles in React using Material-UI Key Features Use React components to build intuitive UI elements Explore a variety of styles and themes in the Material-UI framework using React components Learn practical React recipes and best practices for building modern web applications Book Description Material-UI is a component library for rendering UI elements, using modern best practices from React and Material Design. This book will show you how you can create impressive and captivating modern-day web apps by implementing Material Design considerations. The book is designed to help you use a variety of Material-UI components to enhance UI functionality, along with guiding you through React best practices, and using state, context, and other new React 16.8 features. You will start with layout and navigation, exploring the Grid component and understanding how it’s used to build layouts for your Material-UI apps. Using Material-UI components, you’ll then explore the technique of effectively presenting information. In later sections, you will also learn about the different components for user interactions such as the text input component and buttons. Finally, the book will get you up to speed with customizing the look and feel of your app, right from creating a Material-UI theme through to styling icons and text. By the end of this book, you will have developed the skills you need to improve the look and feel of your applications using Material-UI components. What you will learn Build the overall structure and navigation for your Material-UI app Present simple and complex information in a variety of ways Develop interactive and intuitive controls Group content into sections using tabs and expansion panels Create a general page layout with Material-UI grids Use lists for complex data, and cards for detailed information Who this book is for This book is for React developers who want to implement Material Design principles in their applications. You will also find this book helpful if you are a developer who wants to build a UI using React components without having to build your own UX framework.
    Note: Online resource; Title from title page (viewed March 30, 2019) , Mode of access: World Wide Web.
    URL: https://learning.oreilly.com/library/view/-/9781789615227/?ar
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    Training Systems Using Python Statistical Modeling (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (290 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Leverage the power of Python and statistical modeling techniques for building accurate predictive models Key Features Get started with Python's rich suite of libraries for statistical modeling Implement regression and clustering, and train neural networks from scratch Discover real-world examples on training end-to-end machine learning systems in Python Book Description Python's ease-of-use and multi-purpose nature has made it one of the most popular tools for data scientists and machine learning developers. Its rich libraries are widely used for data analysis, and more importantly, for building state-of-the-art predictive models. This book is designed to guide you through using these libraries to implement effective statistical models for predictive analytics. You'll start by delving into classical statistical analysis, where you will learn to compute descriptive statistics using pandas. You will focus on supervised learning, which will help you explore the principles of machine learning and train different machine learning models from scratch. Next, you will work with binary prediction models, such as data classification using k-nearest neighbors, decision trees, and random forests. The book will also cover algorithms for regression analysis, such as ridge and lasso regression, and their implementation in Python. In later chapters, you will learn how neural networks can be trained and deployed for more accurate predictions, and understand which Python libraries can be used to implement them. By the end of this book, you will have the knowledge you need to design, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive analytics. What you will learn Understand the importance of statistical modeling Learn about the different Python packages for statistical analysis Implement algorithms such as Naive Bayes and random forests Build predictive models from scratch using Python's scikit-learn library Implement regression analysis and clustering Learn how to train a neural network in Python Who this book is for If you are a data scientist, a statistician or a machine learning developer looking to train and deploy effective machine learning models using popular statistical techniques, then this book is for you. Knowledge of Python programming is required to get the most out of this book. Downloading the example code for this ebook: You can download the example code fil...
    Note: Online resource; Title from title page (viewed May 20, 2019) , Mode of access: World Wide Web.
    URL: https://learning.oreilly.com/library/view/-/9781838823733/?ar
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    Developing Java Applications with Spring and Spring Boot (2018)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781789534757
    Language: English
    Pages: 1 online resource (982 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: An end-to-end software development guide for the Java eco-system using the most advanced frameworks: Spring and Spring Boot. Learn the complete workflow by building projects and solving problems. About This Book Learn reactive programming by implementing a reactive application with Spring WebFlux Create a robust and scalable messaging application with Spring messaging support Get up-to-date with the defining characteristics of Spring Boot 2.0 in Spring Framework 5 Learn about developer tools, AMQP messaging, WebSockets, security, MongoDB data access, REST, and more This collection of effective recipes serves as guidelines for Spring Boot application development Who This Book Is For Java developers wanting to build production-grade applications using the newest popular Spring tools for a rich end-to-end application development experience. What You Will Learn Get to know the Spring Boot and understand how it makes creating robust applications extremely simple Understand how Spring Data helps us add persistence in MongoDB and SQL databases Implement a websocket to add interactive behaviors in your applications Create powerful, production-grade applications and services with minimal fuss Use custom metrics to track the number of messages published and consumed Build anything from lightweight unit tests to fully running embedded web container integration tests Learn effective testing techniques by integrating Cucumber and Spock Use Hashicorp Consul and Netflix Eureka for dynamic Service Discovery In Detail Spring Framework has become the most popular framework for Java development. It not only simplifies software development but also improves developer productivity. This book covers effective ways to develop robust applications in Java using Spring. The course is up made of three modules, each one having a take-away relating to building end-to-end java applications. The first module takes the approach of learning Spring frameworks by building applications.You will learn to build APIs and integrate them with popular fraemworks suh as AngularJS, Spring WebFlux, and Spring Data. You will also learn to build microservices using Spring's support for Kotlin. You will learn about the Reactive paradigm in the Spring architecture using Project Reactor. In the second module, after getting hands-on with Spring, you will learn about the most popular tool in the Spring ecosystem-Spring Boot. You will learn to build applications with Spring Boot, bundle them, an...
    Note: Online resource; Title from title page (viewed October 4, 2018) , Mode of access: World Wide Web.
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