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  • 2015-2019  (195)
  • 1935-1939
  • Birmingham, UK : Packt Publishing  (195)
  • JavaScript (Computer program language)  (132)
  • Artificial intelligence  (63)
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Language
Years
Year
Author, Corporation
Publisher
Keywords
Subjects(RVK)
  • 1
    Online Resource
    Online Resource
    TensorFlow reinforcement learning quick start guide : get up and running with training and deploying intelligent, self-learning agents using Python (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789533446 , 1789533449
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: TensorFlow ; Reinforcement learning ; Neural networks (Computer science) ; Python (Computer program language) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Tensorflow to Create powerful software agents that can self-learn to perform real-world tasks Key Features Explore efficient Reinforcement Learning algorithms and code them using TensorFlow and Python Train Reinforcement Learning agents for problems, ranging from computer games to autonomous driving. Formulate and devise selective algorithms and techniques in your applications in no time. Book Description Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving. The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator. By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems. What you will learn Understand the theory and concepts behind modern Reinforcement Learning algorithms Code state-of-the-art Reinforcement Learning algorithms with discrete or continuous actions Develop Reinforcement Learning algorithms and apply them to training agents to play computer games Explore DQN, DDQN, and Dueling architectures to play Atari's Breakout using TensorFlow Use A3C to play CartPole and LunarLander Train an agent to drive a car autonomously in a simulator Who this book is for Data scientists and AI developers who wish to quickly get started with training effective reinforcement learning models in TensorFlow will find this book very useful. Prior knowledge of machine learning and deep learning concepts (...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 14, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789533583/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Hands-on artificial intelligence for IoT : expert machine learning and deep learning techniques for developing smarter IoT systems (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788832762 , 1788832760
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Internet of things ; Artificial intelligence ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Build smarter systems by combining artificial intelligence and the Internet of Things - two of the most talked about topics today Key Features Leverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT data Process IoT data and predict outcomes in real time to build smart IoT models Cover practical case studies on industrial IoT, smart cities, and home automation Book Description There are many applications that use data science and analytics to gain insights from terabytes of data. These apps, however, do not address the challenge of continually discovering patterns for IoT data. In Hands-On Artificial Intelligence for IoT, we cover various aspects of artificial intelligence (AI) and its implementation to make your IoT solutions smarter. This book starts by covering the process of gathering and preprocessing IoT data gathered from distributed sources. You will learn different AI techniques such as machine learning, deep learning, reinforcement learning, and natural language processing to build smart IoT systems. You will also leverage the power of AI to handle real-time data coming from wearable devices. As you progress through the book, techniques for building models that work with different kinds of data generated and consumed by IoT devices such as time series, images, and audio will be covered. Useful case studies on four major application areas of IoT solutions are a key focal point of this book. In the concluding chapters, you will leverage the power of widely used Python libraries, TensorFlow and Keras, to build different kinds of smart AI models. By the end of this book, you will be able to build smart AI-powered IoT apps with confidence. What you will learn Apply different AI techniques including machine learning and deep learning using TensorFlow and Keras Access and process data from various distributed sources Perform supervised and unsupervised machine learning for IoT data Implement distributed processing of IoT data over Apache Spark using the MLLib and H2O.ai platforms Forecast time-series data using deep learning methods Implementing AI from case studies in Personal IoT, Industrial IoT, and Smart Cities Gain unique insights from data obtained from wearable devices and smart devices Who this book is for If you are a data science professional or a machine learning developer looking to build smart systems for IoT, Hands-On Artificial Intelligence for IoT is for you. If you want to learn how po...
    Note: Description based on online resource; title from title page (Safari, viewed March 19, 2019)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Neural network projects with Python : the ultimate guide to using Python to explore the true power of neural networks through six projects (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789133318 , 1789133319
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Neural networks (Computer science) ; Machine learning ; Artificial intelligence ; Electronic books ; local ; Electronic books
    Abstract: Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key Features Discover neural network architectures (like CNN and LSTM) that are driving recent advancements in AI Build expert neural networks in Python using popular libraries such as Keras Includes projects such as object detection, face identification, sentiment analysis, and more Book Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learn Learn various neural network architectures and its advancements in AI Master deep learning in Python by building and training neural network Master neural networks for regression and classification Discover convolutional neural networks for image recognition Learn sentiment analysis on textual data using Long Short-Term Memory Build and train a highly accurate facial recognition security system Who this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.
    Note: Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    Intelligent projects using Python : 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788994866 , 1788994868
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Artificial intelligence ; Machine learning ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key Features A go-to guide to help you master AI algorithms and concepts 8 real-world projects tackling different challenges in healthcare, e-commerce, and surveillance Use TensorFlow, Keras, and other Python libraries to implement smart AI applications Book Description This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. You will assimilate various neural network architectures such as CNN, RNN, LSTM, to solve critical new world challenges. You will learn to train a model to detect diabetic retinopathy conditions in the human eye and create an intelligent system for performing a video-to-text translation. You will use the transfer learning technique in the healthcare domain and implement style transfer using GANs. Later you will learn to build AI-based recommendation systems, a mobile app for sentiment analysis and a powerful chatbot for carrying customer services. You will implement AI techniques in the cybersecurity domain to generate Captchas. Later you will train and build autonomous vehicles to self-drive using reinforcement learning. You will be using libraries from the Python ecosystem such as TensorFlow, Keras and more to bring the core aspects of machine learning, deep learning, and AI. By the end of this book, you will be skilled to build your own smart models for tackling any kind of AI problems without any hassle. What you will learn Build an intelligent machine translation system using seq-2-seq neural translation machines Create AI applications using GAN and deploy smart mobile apps using TensorFlow Translate videos into text using CNN and RNN Implement smart AI Chatbots, and integrate and extend them in several domains Create smart reinforcement, learning-based applications using Q-Learning Break and generate CAPTCHA using Deep Learning and Adversarial Learning Who this book is for This book is intended for data scientists, machine learning professionals, and deep learning practitioners who are ready to extend their knowledge and potential in AI. If you want to build real-life smart systems to play a crucial role in every complex domain, then this book is w...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788996921/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    Deep learning with Microsoft Cognitive Toolkit quick start guide : a practical guide to building neural networks using Microsoft's open source deep learning framework (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789803198 , 1789803195
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Microsoft Cognitive Toolkit ; Neural networks (Computer science) ; Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering how you can use deep learning models in your software applications with Microsoft Cognitive Toolkit Key Features Understand the fundamentals of Microsoft Cognitive Toolkit and set up the development environment Train different types of neural networks using Cognitive Toolkit and deploy it to production Evaluate the performance of your models and improve your deep learning skills Book Description Cognitive Toolkit is a very popular and recently open sourced deep learning toolkit by Microsoft. Cognitive Toolkit is used to train fast and effective deep learning models. This book will be a quick introduction to using Cognitive Toolkit and will teach you how to train and validate different types of neural networks, such as convolutional and recurrent neural networks. This book will help you understand the basics of deep learning. You will learn how to use Microsoft Cognitive Toolkit to build deep learning models and discover what makes this framework unique so that you know when to use it. This book will be a quick, no-nonsense introduction to the library and will teach you how to train different types of neural networks, such as convolutional neural networks, recurrent neural networks, autoencoders, and more, using Cognitive Toolkit. Then we will look at two scenarios in which deep learning can be used to enhance human capabilities. The book will also demonstrate how to evaluate your models' performance to ensure it trains and runs smoothly and gives you the most accurate results. Finally, you will get a short overview of how Cognitive Toolkit fits in to a DevOps environment What you will learn Set up your deep learning environment for the Cognitive Toolkit on Windows and Linux Pre-process and feed your data into neural networks Use neural networks to make effcient predictions and recommendations Train and deploy effcient neural networks such as CNN and RNN Detect problems in your neural network using TensorBoard Integrate Cognitive Toolkit with Azure ML Services for effective deep learning Who this book is for Data Scientists, Machine learning developers, AI developers who wish to train and deploy effective deep learning models using Microsoft CNTK will find this book to be useful. Readers need to have experience in Python or similar object-oriented language like C# or Java.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 8, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789802993/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Hands-on full-stack web development with GraphQL and React : build scalable full-stack applications while learning to solve complex problems with GraphQL (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789135763 , 1789135761
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Application program interfaces (Computer software) ; Application software ; Development ; Web applications ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Unearth the power of GraphQL, React, Apollo, Node, and Express to build a scalable, production ready application Key Features Build full stack applications with modern APIs using GraphQL and Apollo Integrate Apollo into React and build frontend components using GraphQL Implement a self-updating notification pop-up with a unique GraphQL feature called Subscriptions Book Description React, one of the most widely used JavaScript frameworks, allows developers to build fast and scalable front end applications for any use case. GraphQL is the modern way of querying an API. It represents an alternative to REST and is the next evolution in web development. Combining these two revolutionary technologies will give you a future-proof and scalable stack you can start building your business around. This book will guide you in implementing applications by using React, Apollo, Node.js and SQL. We'll focus on solving complex problems with GraphQL, such as abstracting multi-table database architectures and handling image uploads. Our client, and server will be powered by Apollo. Finally we will go ahead and build a complete Graphbook. While building the app, we'll cover the tricky parts of connecting React to the back end, and maintaining and synchronizing state. We'll learn all about querying data and authenticating users. We'll write test cases to verify the front end and back end functionality for our application and cover deployment. By the end of the book, you will be proficient in using GraphQL and React for your full-stack development requirements. What you will learn Resolve data from multi-table database and system architectures Build a GraphQL API by implementing models and schemas with Apollo and Sequelize Set up an Apollo Client and build front end components using React Use Mocha to test your full-stack application Write complex React components and share data across them Deploy your application using Docker Who this book is for The book is for web developers who want to enhance their skills and build complete full stack applications using industry standards. Familiarity with JavaScript, React, and GraphQL is expected to get the most from this book.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789134520/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 7
    Online Resource
    Online Resource
    Hands-on neural networks with Keras : design and create neural networks using deep learning and artificial intelligence principles (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789533347 , 1789533341
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Your one-stop guide to learning and implementing artificial neural networks with Keras effectively Key Features Design and create neural network architectures on different domains using Keras Integrate neural network models in your applications using this highly practical guide Get ready for the future of neural networks through transfer learning and predicting multi network models Book Description Neural networks are used to solve a wide range of problems in different areas of AI and deep learning. Hands-On Neural Networks with Keras will start with teaching you about the core concepts of neural networks. You will delve into combining different neural network models and work with real-world use cases, including computer vision, natural language understanding, synthetic data generation, and many more. Moving on, you will become well versed with convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, autoencoders, and generative adversarial networks (GANs) using real-world training datasets. We will examine how to use CNNs for image recognition, how to use reinforcement learning agents, and many more. We will dive into the specific architectures of various networks and then implement each of them in a hands-on manner using industry-grade frameworks. By the end of this book, you will be highly familiar with all prominent deep learning models and frameworks, and the options you have when applying deep learning to real-world scenarios and embedding artificial intelligence as the core fabric of your organization. What you will learn Understand the fundamental nature and workflow of predictive data modeling Explore how different types of visual and linguistic signals are processed by neural networks Dive into the mathematical and statistical ideas behind how networks learn from data Design and implement various neural networks such as CNNs, LSTMs, and GANs Use different architectures to tackle cognitive tasks and embed intelligence in systems Learn how to generate synthetic data and use augmentation strategies to improve your models Stay on top of the latest academic and commercial developments in the field of AI Who this book is for This book is for machine learning practitioners, deep learning researchers and AI enthusiasts who are looking to get well versed with different neural network architecture using Keras. Working knowledge of Python programming language is mandatory.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 14, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789536089/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 8
    Online Resource
    Online Resource
    React Native cookbook : step-by-step recipes for solving common React Native development problems (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788990431 , 1788990439
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Application software ; Development ; Mobile apps ; Web site development ; JavaScript (Computer program language) ; Web sites ; Design ; Electronic books ; Electronic books ; local
    Abstract: Improve your React Native mobile development skills or transition from web development to mobile development with this practical solution-packed guide Key Features Learn strategies and techniques to face challenges in React Native mobile development head-on Leverage the best ways to use iOS and Android for React Native development while maximizing code reuse and cohesion Build engaging, performant user experiences with React Native Book Description If you are a developer looking to create mobile applications with maximized code reusability and minimized cost, then React Native is here to help. With this practical guide, you will be able to build attractive UIs, tackle common mobile development-related issues, and achieve improved performance in mobile environments. This book starts with common techniques for React Native customization and helps you set up your development platforms. Over the course of the book, a wide variety of step-by-step recipes are designed with both built-in React Native and custom third-party components that you will create, style, and animate. You will create real-world browser-based authentication, build a fully functional audio player, and integrate with Google maps. You will also explore different strategies for working with data, including leveraging the popular Redux library and optimizing your app's dataflow. You will then get an introduction to writing native device functionality for new and already existing native projects. Finally, you will learn how app deployment works, and tips and tricks for writing performant code. By the end of the book, you'll have gained enough knowledge to build full iOS and Android applications using React Native. What you will learn Build UI features and components using React Native Create advanced animations for UI components Develop universal apps that run on phones and tablets Leverage Redux to manage application flow and data Expose both custom native UI components and application logic to React Native Employ open-source third-party plugins to create React Native apps more efficiently Who this book is for If you're a JavaScript developer looking for a practical guide with step-by-step tutorials for developing feature rich mobile apps using React Native, then this book is for you. Though not required, some experience working with React will help you more easily understand the React Native concepts covered in this book. While React Native development can be done on a Windows mach...
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 22, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788991926/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
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  • 9
    Online Resource
    Online Resource
    Create React app 2 quick start guide : build React applications faster with Create React app (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789955668 , 1789955661
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Application software ; Development ; Web applications ; Electronic books ; Electronic books ; local
    Abstract: Integrate your React applications with React to build efficient web services. Key Features Learn React by building applications with Create React App Create interactive UIs exploring the latest feature of CRA 2.0 Build Progressive Web Applications for a more seamless web Book Description If you're a power user and you aren't happy always reusing default configurations, from previous applications with each new application, then all you need is Create React App (CRA), a tool in the React ecosystem designed to help you create boilerplate code for building a web frontend. This book will help you use CRA to write React programs without significant configuration-related difficulties. With this quick start guide, you will integrate your applications with React to build efficient professional web services.You will learn to design UIs with the features of CRA and template your React applications. By the end of the book, you will be sufficiently skilled to be able to build faster and effective React apps using CRA. What you will learn Become familiar with React by building applications with Create React App Make your frontend development hassle free Create interactive UIs exploring the latest features of CRA 2 Build modern, React projects with, SASS,and progressive web applications Develop proxy backend servers and simulate interaction with a full backend Keep your application fully tested and maintain confidence in your project Who this book is for The book is intended for the web developers who want to jump into building great frontend with React using easy templating solutions.
    Note: Description based on online resource; title from title page (Safari, viewed April 10, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789952766/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 10
    Online Resource
    Online Resource
    Python deep learning : exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789349702 , 1789349702
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications across computer vision and NLP Learn how a computer can navigate in complex environments with reinforcement learning Book Description With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you'll explore deep learning, and learn how to put machine learning to use in your projects. This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You'll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You'll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you'll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota. By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications. What you will learn Grasp the mathematical theory behind neural networks and deep learning processes Investigate and resolve computer vision challenges using convolutional networks and capsule networks Solve generative tasks using variational autoencoders and Generative Adversarial Networks Implement complex NLP tasks using recurrent networks (LSTM and GRU) and attention models Explore reinforcement learning and understand how agents behave in a complex environment Get up to date with applications of deep learning in autonomous vehicles Who this book is for This book is for data science practitioners, machine learning engineers, and those interested in deep learning who have a basic foundation in machine learning and some Python programming experience. A background in mathematics and conceptual understandi...
    Note: Description based on online resource; title from title page (Safari, viewed February 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789348460/?ar
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  • 11
    Online Resource
    Online Resource
    Mobile artificial intelligence projects : develop seven projects on your smartphone using artificial intelligence and deep learning techniques (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789347043 , 1789347041
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Mobile apps ; Application software ; Development ; Artificial intelligence ; Machine learning ; Mobile computing ; Electronic books ; Electronic books ; local
    Abstract: Learn to build end-to-end AI apps from scratch for Android and iOS using TensorFlow Lite, CoreML, and PyTorch Key Features Build practical, real-world AI projects on Android and iOS Implement tasks such as recognizing handwritten digits, sentiment analysis, and more Explore the core functions of machine learning, deep learning, and mobile vision Book Description We're witnessing a revolution in Artificial Intelligence, thanks to breakthroughs in deep learning. Mobile Artificial Intelligence Projects empowers you to take part in this revolution by applying Artificial Intelligence (AI) techniques to design applications for natural language processing (NLP), robotics, and computer vision. This book teaches you to harness the power of AI in mobile applications along with learning the core functions of NLP, neural networks, deep learning, and mobile vision. It features a range of projects, covering tasks such as real-estate price prediction, recognizing hand-written digits, predicting car damage, and sentiment analysis. You will learn to utilize NLP and machine learning algorithms to make applications more predictive, proactive, and capable of making autonomous decisions with less human input. In the concluding chapters, you will work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch across Android and iOS platforms. By the end of this book, you will have developed exciting and more intuitive mobile applications that deliver a customized and more personalized experience to users. What you will learn Explore the concepts and fundamentals of AI, deep learning, and neural networks Implement use cases for machine vision and natural language processing Build an ML model to predict car damage using TensorFlow Deploy TensorFlow on mobile to convert speech to text Implement GAN to recognize hand-written digits Develop end-to-end mobile applications that use AI principles Work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch Who this book is for Mobile Artificial Intelligence Projects is for machine learning professionals, deep learning engineers, AI engineers, and software engineers who want to integrate AI technology into mobile-based platforms and applications. Sound knowledge of machine learning and experience with any programming language is all you need to get started with this book.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 14, 2019)
    URL: lizenzpflichtig
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    MPI Ethno. Forsch.
  • 12
    Online Resource
    Online Resource
    Learn Chart.js : create interactive visualizations for the Web with Chart.js 2 (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789342154 , 1789342155
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Charts, diagrams, etc ; Computer programs ; JavaScript (Computer program language) ; Information visualization ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Design interactive graphics and visuals for your data-driven applications using the popular open-source Chart.js data visualization library. Key Features Harness the power of JavaScript, HTML, and CSS to create interactive visualizations Display quantitative information efficiently in the form of attractive charts by using Chart.js A practical guide for creating data-driven applications using open-source JavaScript library Book Description Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library. If you want to quickly create responsive Web-based data visualizations for the Web, Chart.js is a great choice. This book guides the reader through dozens of practical examples, complete with code you can run and modify as you wish. It is a practical hands-on introduction to Chart.js. If you have basic knowledge of HTML, CSS and JavaScript you can learn to create beautiful interactive Web Canvas-based visualizations for your data using Chart.js. This book will help you set up Chart.js in a Web page and show how to create each one of the eight Chart.js chart types. You will also learn how to configure most properties that override Chart's default styles and behaviors. Practical applications of Chart.js are exemplified using real data files obtained from public data portals. You will learn how to load, parse, filter and select the data you wish to display from those files. You will also learn how to create visualizations that reveal patterns in the data. This book is based on Chart.js version 2.7.3 and ES2015 JavaScript. By the end of the book, you will be able to create beautiful, efficient and interactive data visualizations for the Web using Chart.js. What you will learn Learn how to create interactive and responsive data visualizations using Chart.js Learn how to create Canvas-based graphics without Canvas programming Create composite charts and configure animated data updates and transitions Efficiently display quantitative information using bar and line charts, scatterplots, and pie charts Learn how to load, parse, and filter external files in JSON and CSV formats Understand the benefits of using a data visualization framework Who this book is for The ideal target audience of this book includes web developers and designers, data journalists, data scientists and artists who wish to create interactive data visualizations...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789342482/?ar
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  • 13
    Online Resource
    Online Resource
    Redux quick start guide : a beginner's guide to managing app state with Redux (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789806342 , 1789806348
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Application software ; Development ; Web applications ; JavaScript (Computer program language) ; Web sites ; Design ; Electronic books ; Electronic books ; local
    Abstract: Integrate Redux with React and other front-end JavaScript frameworks efficiently and manage application states effectively Key Features Get better at building web applications with state management using Redux Learn the fundamentals of Redux to structure your app more efficiently This guide will teach you develop complex apps that would be easier to maintain Book Description Starting with a detailed overview of Redux, we will follow the test-driven development (TDD) approach to develop single-page applications. We will set up JEST for testing and use JEST to test React, Redux, Redux-Sage, Reducers, and other components. We will then add important middleware and set up immutableJS in our application. We will use common data structures such as Map, List, Set, and OrderedList from the immutableJS framework. We will then add user interfaces using ReactJS, Redux-Form, and Ant Design. We will explore the use of react-router-dom and its functions. We will create a list of routes that we will need in order to create our application, and explore routing on the server site and create the required routes for our application. We will then debug our application and integrate Redux Dev tools. We will then set up our API server and create the API required for our application. We will dive into a modern approach to structuring our server site components in terms of Model, Controller, Helper functions, and utilities functions. We will explore the use of NodeJS with Express to build the REST API components. Finally, we will venture into the possibilities of extending the application for further research, including deployment and optimization. What you will learn Follow the test-driven development (TDD) approach to develop a single-page application Add important middleware, such as Redux store middleware, redux-saga middleware, and language middleware, to your application Understand how to use immutableJS in your application Build interactive components using ReactJS Configure react-router-redux and explore the differences between react-router-dom and react-router-redux Use Redux Dev tools to debug your application Set up our API server and create the API required for our application Who this book is for This book is meant for JavaScript developers interesting in learning state management and building easy to maintain web applications.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789610086/?ar
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  • 14
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    Hands-on unsupervised learning with Python : implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789349276 , 1789349273
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Artificial intelligence ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Discover the skill-sets required to implement various approaches to Machine Learning with Python Key Features Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more Build your own neural network models using modern Python libraries Practical examples show you how to implement different machine learning and deep learning techniques Book Description Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images. By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges. What you will learn Use cluster algorithms to identify and optimize natural groups of data Explore advanced non-linear and hierarchical clustering in action Soft label assignments for fuzzy c-means and Gaussian mixture models Detect anomalies through density estimation Perform principal component analysis using neural network models Create unsupervised models using GANs Who this book is for This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed April 18, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789348279/?ar
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  • 15
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    Generative adversarial networks projects : build next-generation generative models using TensorFlow and Keras (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789134193 , 1789134196
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Explore various Generative Adversarial Network architectures using the Python ecosystem Key Features Use different datasets to build advanced projects in the Generative Adversarial Network domain Implement projects ranging from generating 3D shapes to a face aging application Explore the power of GANs to contribute in open source research and projects Book Description Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you'll gain an understanding of the architecture and functioning of generative models through their practical implementation. By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects. What you will learn Train a network on the 3D ShapeNet dataset to generate realistic shapes Generate anime characters using the Keras implementation of DCGAN Implement an SRGAN network to generate high-resolution images Train Age-cGAN on Wiki-Cropped images to improve face verification Use Conditional GANs for image-to-image translation Understand the generator and discriminator implementations of StackGAN in Keras Who this book is for If you're a data scientist, machine learning developer, deep learning practitioner, or AI enthusiast looking for a project guide to test your knowledge and expertise in building real-world GANs models, this book is for you.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789136678/?ar
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  • 16
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    React design patterns and best practices : design, build and deploy production-ready web applications using standard industry practices (2019)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789534566 , 1789534569
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Application software ; Development ; JavaScript (Computer program language) ; Web applications ; Electronic books ; Electronic books ; local
    Abstract: Build modular React web apps that are scalable, maintainable and powerful using design patterns and insightful practices Key Features Get familiar with design patterns in React like Render props and Controlled/uncontrolled inputs Learn about class/ functional, style and high order components with React Work through examples that can be used to create reusable code and extensible designs Book Description React is an adaptable JavaScript library for building complex UIs from small, detached bits called components. This book is designed to take you through the most valuable design patterns in React, helping you learn how to apply design patterns and best practices in real-life situations. You'll get started by understanding the internals of React, in addition to covering Babel 7 and Create React App 2.0, which will help you write clean and maintainable code. To build on your skills, you will focus on concepts such as class components, stateless components, and pure components. You'll learn about new React features, such as the context API and React Hooks that will enable you to build components, which will be reusable across your applications. The book will then provide insights into the techniques of styling React components and optimizing them to make applications faster and more responsive. In the concluding chapters, you'll discover ways to write tests more effectively and learn how to contribute to React and its ecosystem. By the end of this book, you will be equipped with the skills you need to tackle any developmental setbacks when working with React. You'll be able to make your applications more flexible, efficient, and easy to maintain, thereby giving your workflow a boost when it comes to speed, without reducing quality. What you will learn Get familiar with the new React features,like context API and React Hooks Learn the techniques of styling and optimizing React components Make components communicate with each other by applying consolidate patterns Use server-side rendering to make applications load faster Write a comprehensive set of tests to create robust and maintainable code Build high-performing applications by optimizing components Who this book is for This book is for web developers who want to increase their understanding of React and apply it to real-life application development. Prior experience with React and JavaScript is assumed.
    Note: Previous edition published: 2017. - Description based on online resource; title from title page (Safari, viewed May 14, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789530179/?ar
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  • 17
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    Building large-scale web applications with Angular : your one-stop guide to building scalable and production-grade Angular web apps (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789958324 , 1789958326
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: AngularJS (Software framework) ; Application software ; Development ; Web applications ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: A definitive guide on frontend development with Angular from design to deployment Key Features Develop web applications from scratch using Angular and TypeScript Explore reactive programming principles and RxJS to develop and test apps easily Study continuous integration and deployment on the AWS cloud Book Description If you have been burnt by unreliable JavaScript frameworks before, you will be amazed by the maturity of the Angular platform. Angular enables you to build fast, efficient, and real-world web apps. In this Learning Path, you'll learn Angular and to deliver high-quality and production-grade Angular apps from design to deployment. You will begin by creating a simple fitness app, using the building blocks of Angular, and make your final app, Personal Trainer, by morphing the workout app into a full-fledged personal workout builder and runner with an advanced directive building - the most fundamental and powerful feature of Angular. You will learn the different ways of architecting Angular applications using RxJS, and some of the patterns that are involved in it. Later you'll be introduced to the router-first architecture, a seven-step approach to designing and developing mid-to-large line-of-business apps, along with popular recipes. By the end of this book, you will be familiar with the scope of web development using Angular, Swagger, and Docker, learning patterns and practices to be successful as an individual developer on the web or as a team in the Enterprise. This Learning Path includes content from the following Packt products: Angular 6 by Example by Chandermani Arora, Kevin Hennessy Architecting Angular Applications with Redux, RxJS, and NgRx by Christoffer Noring Angular 6 for Enterprise-Ready Web Applications by Doguhan Uluca What you will learn Develop web applications from scratch using Angular and TypeScript Explore reactive programming principles, RxJS to develop and test apps efficiently Study continuous integration and deployment your Angular app on the AWS cloud Who this book is for If you're a JavaScript or frontend developer looking to gain comprehensive experience of using Angular for end-to-end enterprise-ready applications, this Learning Path is for you.
    Note: Description based on online resource; title from title page (Safari, viewed February 20, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789959567/?ar
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  • 18
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    TensorFlow machine learning projects : build 13 real-world projects with advanced numerical computations using the Python ecosystem (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789132403 , 1789132401
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Implement TensorFlow's offerings such as TensorBoard, TensorFlow.js, TensorFlow Probability, and TensorFlow Lite to build smart automation projects Key Features Use machine learning and deep learning principles to build real-world projects Get to grips with TensorFlow's impressive range of module offerings Implement projects on GANs, reinforcement learning, and capsule network Book Description TensorFlow has transformed the way machine learning is perceived. TensorFlow Machine Learning Projects teaches you how to exploit the benefits - simplicity, efficiency, and flexibility - of using TensorFlow in various real-world projects. With the help of this book, you'll not only learn how to build advanced projects using different datasets but also be able to tackle common challenges using a range of libraries from the TensorFlow ecosystem. To start with, you'll get to grips with using TensorFlow for machine learning projects; you'll explore a wide range of projects using TensorForest and TensorBoard for detecting exoplanets, TensorFlow.js for sentiment analysis, and TensorFlow Lite for digit classification. As you make your way through the book, you'll build projects in various real-world domains, incorporating natural language processing (NLP), the Gaussian process, autoencoders, recommender systems, and Bayesian neural networks, along with trending areas such as Generative Adversarial Networks (GANs), capsule networks, and reinforcement learning. You'll learn how to use the TensorFlow on Spark API and GPU-accelerated computing with TensorFlow to detect objects, followed by how to train and develop a recurrent neural network (RNN) model to generate book scripts. By the end of this book, you'll have gained the required expertise to build full-fledged machine learning projects at work. What you will learn Understand the TensorFlow ecosystem using various datasets and techniques Create recommendation systems for quality product recommendations Build projects using CNNs, NLP, and Bayesian neural networks Play Pac-Man using deep reinforcement learning Deploy scalable TensorFlow-based machine learning systems Generate your own book script using RNNs Who this book is for TensorFlow Machine Learning Projects is for you if you are a data analyst, data scientist, machine learning professional, or deep learning enthusiast with basic knowledge of TensorFlow. This book is also for you if you want to build end-to-end projects in the machine learning domain using ...
    Note: Description based on online resource; title from title page (viewed February 5, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789132212/?ar
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  • 19
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    Deep learning quick reference : useful hacks for training and optimizing deep neural networks with TensorFlow and Keras (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788838917 , 1788838912
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Dive deeper into neural networks and get your models trained, optimized with this quick reference guide About This Book A quick reference to all important deep learning concepts and their implementations Essential tips, tricks, and hacks to train a variety of deep learning models such as CNNs, RNNs, LSTMs, and more Supplemented with essential mathematics and theory, every chapter provides best practices and safe choices for training and fine-tuning your models in Keras and Tensorflow. Who This Book Is For If you are a Data Scientist or a Machine Learning expert, then this book is a very useful read in training your advanced machine learning and deep learning models. You can also refer this book if you are stuck in-between the neural network modeling and need immediate assistance in getting accomplishing the task smoothly. Some prior knowledge of Python and tight hold on the basics of machine learning is required. What You Will Learn Solve regression and classification challenges with TensorFlow and Keras Learn to use Tensor Board for monitoring neural networks and its training Optimize hyperparameters and safe choices/best practices Build CNN's, RNN's, and LSTM's and using word embedding from scratch Build and train seq2seq models for machine translation and chat applications. Understanding Deep Q networks and how to use one to solve an autonomous agent problem. Explore Deep Q Network and address autonomous agent challenges. In Detail Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It moves deep learning from academia to the real world through practical examples. You will learn how Tensor Board is used to monitor the training of deep neural networks and solve binary classification problems using deep learning. Readers will then learn to optimize hyperparameters in their deep learning models. The book then takes the readers through the practical implementation of training CNN's, RNN's, and LSTM's with word embeddings and seq2seq models from scratch. Later the book explores advanced topics such as Deep Q Network to solve an autonomous agent problem and how to use two adversarial networks to generate artificial images that appear real. For implementation purposes, we look at popular Python-based deep learning frameworks such as Keras and Tensorflow, Each chapter provides best pr...
    Note: Description based on online resource; title from title page (Safari, viewed May 7, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788837996/?ar
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  • 20
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    TensorFlow machine learning cookbook : over 60 recipes to build intelligent machine learning systems with the power of Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789130768 , 178913076X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Machine learning ; Artificial intelligence ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Skip the theory and get the most out of Tensorflow to build production-ready machine learning models Key Features Exploit the features of Tensorflow to build and deploy machine learning models Train neural networks to tackle real-world problems in Computer Vision and NLP Handy techniques to write production-ready code for your Tensorflow models Book Description TensorFlow is an open source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and allow you to dig deeper and gain more insights into your data than ever before. With the help of this book, you will work with recipes for training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and more. You will explore RNNs, CNNs, GANs, reinforcement learning, and capsule networks, each using Google's machine learning library, TensorFlow. Through real-world examples, you will get hands-on experience with linear regression techniques with TensorFlow. Once you are familiar and comfortable with the TensorFlow ecosystem, you will be shown how to take it to production. By the end of the book, you will be proficient in the field of machine intelligence using TensorFlow. You will also have good insight into deep learning and be capable of implementing machine learning algorithms in real-world scenarios. What you will learn Become familiar with the basic features of the TensorFlow library Get to know Linear Regression techniques with TensorFlow Learn SVMs with hands-on recipes Implement neural networks to improve predictive modeling Apply NLP and sentiment analysis to your data Master CNN and RNN through practical recipes Implement the gradient boosted random forest to predict housing prices Take TensorFlow into production Who this book is for If you are a data scientist or a machine learning engineer with some knowledge of linear algebra, statistics, and machine learning, this book is for you. If you want to skip the theory and build production-ready machine learning models using Tensorflow without reading pages and pages of material, this book is for you. Some background in Python programming is assumed. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/s...
    Note: Previous edition published: 2017. - Description based on online resource; title from title page (Safari, viewed October 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789131680/?ar
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  • 21
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    AI blueprints : how to build and deploy AI business projects (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788997973 , 1788997972
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Expert insight
    Keywords: Application software ; Development ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: The essential blueprints and workflow you need to build successful AI business applications Key Features Learn and master the essential blueprints to program AI for real-world business applications Gain insights into how modern AI and machine learning solve core business challenges Acquire practical techniques and a workflow that can build AI applications using state-of-the-art software libraries Work with a practical, code-based strategy for creating successful AI solutions in your business Book Description AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You'll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you'll discover the practical techniques to build AI business applications from first design to full coding and deployment. The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You'll learn how to approach AI business problems and apply blueprints that can ensure success. The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a 'trending now' section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers' questions and answer them with relevant responses. This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you'll also learn how to prepare for future advances in AI. You'll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code. What you will learn An essential toolbox of blueprints and advanced techniques for building AI business applications How to design and deploy AI applicati...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed February 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788992879/?ar
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  • 22
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    Hands-on artificial intelligence for beginners : an introduction to AI concepts, algorithms, and their implementation (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788992268 , 1788992261
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Grasp the fundamentals of Artificial Intelligence and build your own intelligent systems with ease Key Features Enter the world of AI with the help of solid concepts and real-world use cases Explore AI components to build real-world automated intelligence Become well versed with machine learning and deep learning concepts Book Description Virtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world. Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games. By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications. What you will learn Use TensorFlow packages to create AI systems Build feedforward, convolutional, and recurrent neural networks Implement generative models for text generation Build reinforcement learning algorithms to play games Assemble RNNs, CNNs, and decoders to create an intelligent assistant Utilize RNNs to predict stock market behavior Create and scale training pipelines and deployment architectures for AI systems Who this book is for This book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 20, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788991063/?ar
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  • 23
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    Unity 2018 artificial intelligence cookbook : over 90 recipes to build and customize AI entities for your games with Unity (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788625227 , 1788625226
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Unity (Electronic resource) ; Computer games ; Programming ; Artificial intelligence ; Three-dimensional display systems ; Electronic books ; Electronic books ; local
    Abstract: Explore various recipes to build games using popular artificial intelligence techniques and algorithms such as Navmesh navigation A*, DFS, and UCB1 Key Features Explore different algorithms for creating decision-making agents that go beyond simple behaviors and movement Discover the latest features of the NavMesh API for scripting intelligent behaviour in your game characters Create games that are non-predictable and dynamic and have a high replayability factor Book Description Interactive and engaging games come with intelligent enemies, and this intellectual behavior is combined with a variety of techniques collectively referred to as Artificial Intelligence. Exploring Unity's API, or its built-in features, allows limitless possibilities when it comes to creating your game's worlds and characters. This cookbook covers both essential and niche techniques to help you take your AI programming to the next level. To start with, you'll quickly run through the essential building blocks of working with an agent, programming movement, and navigation in a game environment, followed by improving your agent's decision-making and coordination mechanisms - all through hands-on examples using easily customizable techniques. You'll then discover how to emulate the vision and hearing capabilities of your agent for natural and humanlike AI behavior, and later improve the agents with the help of graphs. This book also covers the new navigational mesh with improved AI and pathfinding tools introduced in the Unity 2018 update. You'll empower your AI with decision-making functions by programming simple board games, such as tic-tac-toe and checkers, and orchestrate agent coordination to get your AIs working together as one. By the end of this book, you'll have gained expertise in AI programming and developed creative and interactive games. What you will learn Create intelligent pathfinding agents with popular AI techniques such as A* and A*mbush Implement different algorithms for adding coordination between agents and tactical algorithms for different purposes Simulate senses so agents can make better decisions, taking account of the environment Explore different algorithms for creating decision-making agents that go beyond simple behaviors and movement Create coordination between agents and orchestrate tactics when dealing with a graph or terrain Implement waypoints by making a manual selector Who this book is for The Unity 2018 Artificial Intelligence Cookbook i...
    Note: Description based on online resource; title from title page (viewed September 11, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788626170/?ar
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  • 24
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    Practical test-driven development using C# 7 : unleash the power of TDD by implementing real world examples under .NET environment and JavaScript (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788390606 , 1788390601
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Microsoft .NET Framework ; C# (Computer program language) ; JavaScript (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Develop applications for the real world with a thorough software testing approach About This Book Develop a thorough understanding of TDD and how it can help you develop simpler applications with no defects using C# and JavaScript Adapt to the mindset of writing tests before code by incorporating business goals, code manageability, and other factors Make all your software units and modules pass tests by analyzing failed tests and refactoring code as and when required Who This Book Is For This book is for software developers with a basic knowledge of Test Driven Development (TDD) who want a thorough understanding of how TDD can benefit them and the applications they produce. The examples in this book are in C#, and you will need a basic understanding of C# to work through these examples. What You Will Learn The core concepts of TDD Testing in action with a real-world case study in C# and JavaScript using React Writing proper Unit Tests and testable code for your application Using different types of test double such as stubs, spies, and mocks Growing an application guided by tests Exploring new developments on a green-field application Mitigating the problems associated with writing tests for legacy applications Modifying a legacy application to make it testable In Detail Test-Driven Development (TDD) is a methodology that helps you to write as little as code as possible to satisfy software requirements, and ensures that what you've written does what it's supposed to do. If you're looking for a practical resource on Test-Driven Development this is the book for you. You've found a practical end-to-end guide that will help you implement Test-Driven Techniques for your software development projects. You will learn from industry standard patterns and practices, and shift from a conventional approach to a modern and efficient software testing approach in C# and JavaScript. This book starts with the basics of TDD and the components of a simple unit test. Then we look at setting up the testing framework so that you can easily run your tests in your development environment. You will then see the importance of defining and testing boundaries, abstracting away third-party code (including the .NET Framework), and working with different types of test double such as spies, mocks, and fakes. Moving on, you will learn how to think like a TDD developer when it comes to application development. Next, you'll focus on writing tests for new/changing requirements an...
    Note: Description based on online resource; title from title page (Safari, viewed March 7, 2018)
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  • 25
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    Hands-on data structures and algorithms with JavaScript : write efficient code that is highly performant, scalable, and easily testable using JavaScript (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788397544 , 1788397541
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Data structures (Computer science) ; Computer algorithms ; Electronic books ; Electronic books ; local
    Abstract: Increase your productivity by implementing complex data structures and algorithms using JavaScript About This Book A step by step guide, which will provide you with a thorough discussion on the analysis and design of fundamental JavaScript data structures Get a better understanding of advanced concepts such as space and time complexity to optimize your code Focus more on solving the business problem and less on the technical challenges involved Who This Book Is For If you are a JavaScript developer looking for practical examples to implement data structures and algorithms in your web applications, then this book is for you. Familiarity with data structures and algorithms will be helpful to get the most out of this book. What You Will Learn Build custom Back buttons embedded within your application Build part of a basic JavaScript syntax parser and evaluator for an online IDE Build a custom activity user tracker for your application Generate accurate recommendations for credit card approval using Decision Trees Simplify complex problems using a graphs Increase the performance of an application using micro-optimizations In Detail Data structures and algorithms are the fundamental building blocks of computer programming. They are critical to any problem, provide a complete solution, and act like reusable code. Using appropriate data structures and having a good understanding of algorithm analysis are key in JavaScript to solving crises and ensuring your application is less prone to errors. Do you want to build applications that are high-performing and fast? Are you looking for complete solutions to implement complex data structures and algorithms in a practical way? If either of these questions rings a bell, then this book is for you! You'll start by building stacks and understanding performance and memory implications. You will learn how to pick the right type of queue for the application. You will then use sets, maps, trees, and graphs to simplify complex applications. You will learn to implement different types of sorting algorithm before gradually calculating and analyzing space and time complexity. Finally, you'll increase the performance of your application using micro optimizations and memory management. By the end of the book you will have gained the skills and expertise necessary to create and employ various data structures in a way that is demanded by your project or use case. Style and approach Step-by-step topics will help you get sta...
    Note: Description based on online resource; title from title page (Safari, viewed February 22, 2018)
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    MobX quick start guide : supercharge the client state in your React apps with MobX (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789348972 , 1789348978
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Application software ; Development ; Web applications ; Information technology ; Management ; Electronic books ; Electronic books ; local
    Abstract: Apply functional Reactive programming for simple and scalable state management with MobX Key Features The easiest way to learn MobX to enhance your client-side state-management Understand how the concepts and components fit together Work through different state management scenarios with MobX Book Description MobX is a simple and highly scalable state management library in JavaScript. Its abstractions can help you manage state in small to extremely large applications. However, if you are just starting out, it is essential to have a guide that can help you take the first steps. This book aims to be that guide that will equip you with the skills needed to use MobX and effectively handle the state management aspects of your application. You will first learn about observables, actions, and reactions: the core concepts of MobX. To see how MobX really shines and simplifies state management, you'll work through some real-world use cases. Building on these core concepts and use cases, you will learn about advanced MobX, its APIs, and libraries that extend MobX. By the end of this book, you will not only have a solid conceptual understanding of MobX, but also practical experience. You will gain the confidence to tackle many of the common state management problems in your own projects. What you will learn Explore the fundamental concepts of MobX, such as observables, actions, and reactions Use observables to track state and react to its changes with validations and visual feedback (via React Components) Create a MobX observable from different data types Define form data as an observable state and tackle sync and async form validations Use the special APIs to directly manipulate observables, tracking its changes, and discovering the reasons behind a change Tackle any state management issue you may have in your app by combining mobx-utils and mobx-state-tree Explore the internals of the MobX reactive system by diving into its inner workings Who this book is for This book is for web developers who want to implement easy and scalable state management for their apps. Knowledge of HTML, CSS, and JavaScript is assumed Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed August 28, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789344837/?ar
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    Hands-on meta learning with Python : meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789537024 , 1789537029
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Explore a diverse set of meta-learning algorithms and techniques to enable human-like cognition for your machine learning models using various Python frameworks Key Features Understand the foundations of meta learning algorithms Explore practical examples to explore various one-shot learning algorithms with its applications in TensorFlow Master state of the art meta learning algorithms like MAML, reptile, meta SGD Book Description Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster. Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning. By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models. What you will learn Understand the basics of meta learning methods, algorithms, and types Build voice and face recognition models using a siamese network Learn the prototypical network along with its variants Build relation networks and matching networks from scratch Implement MAML and Reptile algorithms from scratch in Python Work through imitation learning and adversarial meta learning Explore task agnostic meta learning and deep meta learning Who this book is for Hands-On Meta Learning with Python is for machine learning enthusiasts, AI researchers, and data scientists who want to explore meta learning as an advanced approach for training machine learning models. Working knowledge of machine learning concepts and Python programming is necessary.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789534207/?ar
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  • 28
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    Unity artificial intelligence programming : add powerful, believable, and fun AI entities in your game with the power of Unity 2018! (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789531459 , 1789531454
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Fourth edition.
    Keywords: Unity (Electronic resource) ; Computer games ; Programming ; Artificial intelligence ; Three-dimensional display systems ; Electronic books ; Electronic books ; local
    Abstract: Learn and Implement game AI in Unity 2018 to build smart game environments and enemies with A*, Finite State Machines, Behavior Trees and NavMesh. Key Features Build richer games by learning the essential concepts in AI for games like Behavior Trees and Navigation Meshes Implement character behaviors and simulations using the Unity Machine Learning toolkit Explore the latest Unity 2018 features to make implementation of AI in your game easier Book Description Developing Artificial Intelligence (AI) for game characters in Unity 2018 has never been easier. Unity provides game and app developers with a variety of tools to implement AI, from the basic techniques to cutting-edge machine learning-powered agents. Leveraging these tools via Unity's API or built-in features allows limitless possibilities when it comes to creating your game's worlds and characters. This fourth edition with Unity will help you break down AI into simple concepts to give you a fundamental understanding of the topic to build upon. Using a variety of examples, the book then takes those concepts and walks you through actual implementations designed to highlight key concepts and features related to game AI in Unity. Further on, you'll learn how to distinguish the state machine pattern and implement one of your own. This is followed by learning how to implement a basic sensory system for your AI agent and coupling it with a Finite State Machine (FSM). Next, you'll learn how to use Unity's built-in NavMesh feature and implement your own A* pathfinding system. You'll then learn how to implement simple ?ocks and crowd dynamics, which are key AI concepts in Unity. Moving on, you'll learn how to implement a behavior tree through a game-focused example. Lastly, you'll apply all the concepts in the book to build a popular game. What you will learn Create smarter game worlds and characters with C# programming Apply automated character movement using pathfinding and steering behaviors Implement non-player character decision-making algorithms using Behavior Trees and FSMs Build believable and highly efficient artificial flocks and crowds Create sensory systems for your AI with the most commonly used techniques Construct decision-making systems to make agents take different actions Explore the application of machine learning in Unity Who this book is for This book is intended for Unity developers with a basic understanding of C# and the Unity editor. Whether you're looking to build your f...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 1, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789533910/?ar
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    Artificial intelligence for robotics : build intelligent robots that perform human tasks using AI techniques (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788835701 , 1788835700
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Robots ; Programming ; Robotics ; Artificial intelligence ; Natural language processing (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Bring a new degree of interconnectivity to your world by building your own intelligent robots Key Features Leverage fundamentals of AI and robotics Work through use cases to implement various machine learning algorithms Explore Natural Language Processing (NLP) concepts for efficient decision making in robots Book Description Artificial Intelligence for Robotics starts with an introduction to Robot Operating Systems (ROS), Python, robotic fundamentals, and the software and tools that are required to start out with robotics. You will learn robotics concepts that will be useful for making decisions, along with basic navigation skills. As you make your way through the chapters, you will learn about object recognition and genetic algorithms, which will teach your robot to identify and pick up an irregular object. With plenty of use cases throughout, you will explore natural language processing (NLP) and machine learning techniques to further enhance your robot. In the concluding chapters, you will learn about path planning and goal-oriented programming, which will help your robot prioritize tasks. By the end of this book, you will have learned to give your robot an artificial personality using simulated intelligence. What you will learn Get started with robotics and artificial intelligence Apply simulation techniques to give your robot an artificial personality Understand object recognition using neural networks and supervised learning techniques Pick up objects using genetic algorithms for manipulation Teach your robot to listen using NLP via an expert system Use machine learning and computer vision to teach your robot how to avoid obstacles Understand path planning, decision trees, and search algorithms in order to enhance your robot Who this book is for If you have basic knowledge about robotics and want to build or enhance your existing robot's intelligence, then Artificial Intelligence for Robotics is for you. This book is also for enthusiasts who want to gain knowledge of AI and robotics.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed October 8, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788835442/?ar
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  • 30
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    Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788839303 , 1788839307
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Reinforcement learning ; Machine learning ; Natural language processing (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. About This Book Explore deep reinforcement learning (RL), from the first principles to the latest algorithms Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithms Keep up with the very latest industry developments, including AI-driven chatbots Who This Book Is For Some fluency in Python is assumed. Basic deep learning (DL) approaches should be familiar to readers and some practical experience in DL will be helpful. This book is an introduction to deep reinforcement learning (RL) and requires no background in RL. What You Will Learn Understand the DL context of RL and implement complex DL models Learn the foundation of RL: Markov decision processes Evaluate RL methods including Cross-entropy, DQN, Actor-Critic, TRPO, PPO, DDPG, D4PG and others Discover how to deal with discrete and continuous action spaces in various environments Defeat Atari arcade games using the value iteration method Create your own OpenAI Gym environment to train a stock trading agent Teach your agent to play Connect4 using AlphaGo Zero Explore the very latest deep RL research on topics including AI-driven chatbots In Detail Recent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google's use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace. Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on 'grid world' environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots. Style and approach Deep Reinforcement Learning Hands-On explains the art of building self-learning agents using algori...
    Note: "Expert insight.". - Includes bibliographical references and index. - Description based on online resource; title from cover (Safari, viewed July 30, 2018)
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    Deep learning with TensorFlow : explore neural networks and build intelligent systems with Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788831833 , 1788831837
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition, fully revised and updated.
    Keywords: Machine learning ; Artificial intelligence ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow. About This Book Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide Gain real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is for people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn Apply deep machine intelligence and GPU computing with TensorFlow Access public datasets and use TensorFlow to load, process, and transform the data Discover how to use the high-level TensorFlow API to build more powerful applications Use deep learning for scalable object detection and mobile computing Train machines quickly to learn from data by exploring reinforcement learning techniques Explore active areas of deep learning research and applications In Detail Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being used in predictive analytics, computer vision, natural language processing, time series forecasting, and to perform a myriad of other complex tasks. This book is conceived for developers, data analysts, machine learning practitioners and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. Throughout the book, you'll learn how to develop deep learning applications for machine learning systems using Feedforward Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Factorization Machines. Discover how to attain deep learning programming on GPU in a distributed way. You'll come away with an in-depth knowledge of machine learning techniques and the skills to apply them to real-world projects. Style and approach This step-by-step guide explores common, and not so common, deep neural networks, and shows ho...
    Note: Includes index. - Description based on online resource; title from cover (Safari, viewed May 8, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788831109/?ar
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    Real-time 3D graphics with WebGL 2 : build interactive 3D applications with JavaScript and WebGL 2 (OpenGL ES 3.0) (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788837873 , 1788837878
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: JavaScript (Computer program language) ; WebGL (Computer program language) ; Three-dimensional modeling ; Computer graphics ; Electronic books ; Electronic books ; local
    Abstract: A comprehensive guide with 80+ examples on 3D programming in WebGL 2, covering computer graphics topics such as rendering, 3D math, camera, and more Key Features Create visually stunning, high-performance 3D applications for the web with WebGL 2 A complete course on 3D computer graphics: rendering, 3D math, lighting, cameras, and more Unlock a variety of new and advanced features offered in WebGL 2 Book Description As highly interactive applications have become an increasingly important part of the user experience, WebGL is a unique and cutting-edge technology that brings hardware-accelerated 3D graphics to the web. Packed with 80+ examples, this book guides readers through the landscape of real-time computer graphics using WebGL 2. Each chapter covers foundational concepts in 3D graphics programming with various implementations. Topics are always associated with exercises for a hands-on approach to learning. This book presents a clear roadmap to learning real-time 3D computer graphics with WebGL 2. Each chapter starts with a summary of the learning goals for the chapter, followed by a detailed description of each topic. The book offers example-rich, up-to-date introductions to a wide range of essential 3D computer graphics topics, including rendering, colors, textures, transformations, framebuffers, lights, surfaces, blending, geometry construction, advanced techniques, and more. With each chapter, you will "level up" your 3D graphics programming skills. This book will become your trustworthy companion in developing highly interactive 3D web applications with WebGL and JavaScript. What you will learn Understand the rendering pipeline provided in WebGL Build and render 3D objects with WebGL Develop lights using shaders, 3D math, and the physics of light reflection Create a camera and use it to navigate a 3D scene Use texturing, lighting, and shading techniques to render realistic 3D scenes Implement object selection and interaction in a 3D scene Cover advanced techniques for creating immersive and compelling scenes Learn new and advanced features offered in WebGL 2 Who this book is for This book is intended for developers who are interested in building highly interactive 3D applications for the web. A basic understanding of JavaScript is necessary; no prior computer graphics or WebGL knowledge is required.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed December 10, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788629690/?ar
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    Mastering SVG : ace web animations, visualizations, and vector graphics with HTML, CSS, and JavaScript (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788621984 , 1788621980
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: SVG (Document markup language) ; JavaScript (Computer program language) ; Computer graphics ; Web sites ; Design ; Electronic books ; Electronic books ; local
    Abstract: Take the plunge and develop cross-browser-compatible and responsive web designs with SVG Key Features Master the art of custom animations and visualizations with SVG, CSS, and JavaScript Combine SVG with third-party libraries and frameworks such as React, JQuery, D3, and Snap.svg for GUI-rich apps Create an awesome user experience with high-performance graphics for your web applications Book Description SVG is the most powerful image format in use on the web. In addition to producing resolution-independent images for today's multi-device world, SVG allows you to create animations and visualizations to add to your sites and applications. The simplicity of cross-platform markup, mixed with familiar modern web languages, such as CSS and JavaScript, creates a winning combination for designers and developers alike. In this book, you will learn how to author an SVG document using common SVG features, such as elements and attributes, and serve SVG on the web using simple configuration tips for common web servers. You will also use SVG elements and images in HTML documents. Further, you will use SVG images for a variety of common tasks, such as manipulating SVG elements, adding animations using CSS, mastering the basic JavaScript SVG (API) using Document Object Model (DOM) methods, and interfacing SVG with common libraries and frameworks, such as React, jQuery, and Angular. You will then build an understanding of the Snap.svg and SVG.js APIs, along with the basics of D3, and take a look at how to implement interesting visualizations using the library. By the end of the book, you will have mastered creating animations with SVG. What you will learn Deliver the elements that make up an SVG image Replace your old CSS sprites with SVG Understand animation and data visualization with SVG are explained in pure JavaScript and using common libraries Use SVG to scale images across multiple devices easily Harness the power of CSS animations and transformations to manipulate your SVG images in a replicable, remixable way Interface SVG with common libraries and frameworks, such as jQuery, React, and Angular Who this book is for This book is for web developers and designers looking to add animation to their projects. Some experience with HTML, CSS, and JavaScript is required.
    Note: Description based on online resource; title from title page (Safari, viewed October 25, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788626743/?ar
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    Learn ECMAScript : discover the latest ECMAScript features in order to write cleaner code and learn the fundamentals of JavaScript (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788629621 , 1788629620
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: JavaScript (Computer program language) ; Application software ; Design ; Electronic books ; Electronic books ; local
    Abstract: Get up and running with all the new features of ECMAScript and explore new ways of coding with JavaScript. About This Book Grasp the latest features of ECMAScript and the best way to use it in production code Learn newly added native APIs to JS Engine and perform tasks efficiently with a cleaner code base Understand the more complex sides of JavaScript such as the inheritance model, low-level memory management, multithreaded environments, and web workers Who This Book Is For This book is for web developers who have some basic programming knowledge and want to learn to write cleaner code with the power of ECMAScript. What You Will Learn Implement methods associated with objects as per the latest ECMAScript specification Make use of the latest features of ECMAScript Make use of many new APIs in HTML5 and modern JavaScript implementation Use SharedArrayBuffers for superfast concurrent and parallel programming Perform asynchronous programming with JavaScript Implement the best ways and practices to perform modular programming in JavaScript In Detail Learn ECMAScript explores implementation of the latest ECMAScript features to add to your developer toolbox, helping you to progress to an advanced level. Learn to add 1 to a variable andsafely access shared memory data within multiple threads to avoid race conditions. You'll start the book by building on your existing knowledge of JavaScript, covering performing arithmetic operations, using arrow functions and dealing with closures. Next, you will grasp the most commonly used ECMAScript skills such as reflection, proxies, and classes. Furthermore, you'll learn modularizing the JS code base, implementing JS on the web and how the modern HTML5 + JS APIs provide power to developers on the web. Finally, you will learn the deeper parts of the language, which include making JavaScript multithreaded with dedicated and shared web workers, memory management, shared memory, and atomics. It doesn't end here; this book is 100% compatible with ES.Next. By the end of this book, you'll have fully mastered all the features of ECMAScript! Style and approach The level goes gradually from basic to advanced so that the reader can adapt at every point and level up their skills at the same time. The chapters are carefully arranged in a manner that makes every concept easy to learn and deploy right away in your code.
    Note: Description based on online resource; title from title page (viewed April 2, 2018)
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    Building enterprise JavaScript applications : learn to build and deploy robust JavaScript applications using Cucumber, Mocha, Jenkins, Docker, and Kubernetes (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788472913 , 1788472918
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Web site development ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Become a senior developer by building enterprise applications that use modern techniques such as TDD, containerization, continuous integration, and deployment Key Features Create production-grade JavaScript applications from scratch Build microservices and deploy them to a Docker container for scaling applications Test and deploy your code with confidence using Travis CI Book Description With the over-abundance of tools in the JavaScript ecosystem, it's easy to feel lost. Build tools, package managers, loaders, bundlers, linters, compilers, transpilers, typecheckers - how do you make sense of it all? In this book, we will build a simple API and React application from scratch. We begin by setting up our development environment using Git, yarn, Babel, and ESLint. Then, we will use Express, Elasticsearch and JSON Web Tokens (JWTs) to build a stateless API service. For the front-end, we will use React, Redux, and Webpack. A central theme in the book is maintaining code quality. As such, we will enforce a Test-Driven Development (TDD) process using Selenium, Cucumber, Mocha, Sinon, and Istanbul. As we progress through the book, the focus will shift towards automation and infrastructure. You will learn to work with Continuous Integration (CI) servers like Jenkins, deploying services inside Docker containers, and run them on Kubernetes. By following this book, you would gain the skills needed to build robust, production-ready applications. What you will learn Practice Test-Driven Development (TDD) throughout the entire book Use Cucumber, Mocha and Selenium to write E2E, integration, unit and UI tests Build stateless APIs using Express and Elasticsearch Document your API using OpenAPI and Swagger Build and bundle front-end applications using React, Redux and Webpack Containerize services using Docker Deploying scalable microservices using Kubernetes Who this book is for If you're a JavaScript developer looking to expand your skillset and become a senior JavaScript developer by building production-ready web applications, then this book is for you. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Description based on online resource; title from title page (Safari, viewed November 2, 2018)
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    Deep learning with PyTorch : a practical approach to building neural network models using PyTorch (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788626071 , 1788626079
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Machine learning ; Python (Computer program language) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Build neural network models in text, vision and advanced analytics using PyTorch About This Book Learn PyTorch for implementing cutting-edge deep learning algorithms. Train your neural networks for higher speed and flexibility and learn how to implement them in various scenarios; Cover various advanced neural network architecture such as ResNet, Inception, DenseNet and more with practical examples; Who This Book Is For This book is for machine learning engineers, data analysts, data scientists interested in deep learning and are looking to explore implementing advanced algorithms in PyTorch. Some knowledge of machine learning is helpful but not a mandatory need. Working knowledge of Python programming is expected. What You Will Learn Use PyTorch for GPU-accelerated tensor computations Build custom datasets and data loaders for images and test the models using torchvision and torchtext Build an image classifier by implementing CNN architectures using PyTorch Build systems that do text classification and language modeling using RNN, LSTM, and GRU Learn advanced CNN architectures such as ResNet, Inception, Densenet, and learn how to use them for transfer learning Learn how to mix multiple models for a powerful ensemble model Generate new images using GAN's and generate artistic images using style transfer In Detail Deep learning powers the most intelligent systems in the world, such as Google Voice, Siri, and Alexa. Advancements in powerful hardware, such as GPUs, software frameworks such as PyTorch, Keras, Tensorflow, and CNTK along with the availability of big data have made it easier to implement solutions to problems in the areas of text, vision, and advanced analytics. This book will get you up and running with one of the most cutting-edge deep learning libraries-PyTorch. PyTorch is grabbing the attention of deep learning researchers and data science professionals due to its accessibility, efficiency and being more native to Python way of development. You'll start off by installing PyTorch, then quickly move on to learn various fundamental blocks that power modern deep learning. You will also learn how to use CNN, RNN, LSTM and other networks to solve real-world problems. This book explains the concepts of various state-of-the-art deep learning architectures, such as ResNet, DenseNet, Inception, and Seq2Seq, without diving deep into the math behind them. You will also learn about GPU computing during the course of the book. You will see how ...
    Note: Description based on online resource; title from title page (Safari, viewed March 13, 2018)
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    Keras deep learning cookbook : over 30 recipes for implementing deep neural networks in Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788623087 , 1788623088
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of deep learning and Keras to develop smarter and more efficient data models Key Features Understand different neural networks and their implementation using Keras Explore recipes for training and fine-tuning your neural network models Put your deep learning knowledge to practice with real-world use-cases, tips, and tricks Book Description Keras has quickly emerged as a popular deep learning library. Written in Python, it allows you to train convolutional as well as recurrent neural networks with speed and accuracy. The Keras Deep Learning Cookbook shows you how to tackle different problems encountered while training efficient deep learning models, with the help of the popular Keras library. Starting with installing and setting up Keras, the book demonstrates how you can perform deep learning with Keras in the TensorFlow. From loading data to fitting and evaluating your model for optimal performance, you will work through a step-by-step process to tackle every possible problem faced while training deep models. You will implement convolutional and recurrent neural networks, adversarial networks, and more with the help of this handy guide. In addition to this, you will learn how to train these models for real-world image and language processing tasks. By the end of this book, you will have a practical, hands-on understanding of how you can leverage the power of Python and Keras to perform effective deep learning What you will learn Install and configure Keras in TensorFlow Master neural network programming using the Keras library Understand the different Keras layers Use Keras to implement simple feed-forward neural networks, CNNs and RNNs Work with various datasets and models used for image and text classification Develop text summarization and reinforcement learning models using Keras Who this book is for Keras Deep Learning Cookbook is for you if you are a data scientist or machine learning expert who wants to find practical solutions to common problems encountered while training deep learning models. A basic understanding of Python and some experience in machine learning and neural networks is required for this book.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 11, 2019)
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    Learning Node.js development : learn the fundamentals of Node.js, and deploy and test Node.js applications on the web (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788396349 , 1788396340
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Web applications ; Development ; Web site development ; Electronic books ; Electronic books ; local
    Abstract: A comprehensive, easy-to-follow guide to creating complete Node apps and understanding how to build, deploy, and test your own apps. About This Book Entirely project-based and practical Explains the "Why" of Node.js features, not just the "how", providing you with a deep understanding and enabling you to easily apply concepts in your own applications Covers the full range of technologies around Node.js - NPM, version control with Git, and much more Who This Book Is For This book targets anyone looking to launch their own Node applications, switch careers, or freelance as a Node developer. You should have a basic understanding of JavaScript in order to follow this course. What You Will Learn Learn the fundamentals of Node Build apps that respond to user input Master working with servers Learn how to test and debug applications Deploy and update your apps in the real world Create responsive asynchronous web applications In Detail Learning Node.js Development is a practical, project-based book that provides you with all you need to get started as a Node.js developer. Node is a ubiquitous technology on the modern web, and an essential part of any web developers' toolkit. If you are looking to create real-world Node applications, or you want to switch careers or launch a side project to generate some extra income, then you're in the right place. This book has been written around a single goal-turning you into a professional Node developer capable of developing, testing, and deploying real-world production applications. Learning Node.js Development is built from the ground up around the latest version of Node.js (version 9.x.x). You'll be learning all the cutting-edge features available only in the latest software versions. This book cuts through the mass of information available around Node and delivers the essential skills that you need to become a Node developer. It takes you through creating complete apps and understanding how to build, deploy, and test your own Node apps. It maps out everything in a comprehensive, easy-to-follow package designed to get you up and running quickly. Style and approach This book is entirely project-based. From the very beginning you'll be programming every single app and completing various challenges designed to help test and reinforce what you've learned. There's no copying-and-pasting here. This book is about writing code and building projects. Downloading the example code for this book You can download the examp...
    Note: Description based on online resource; title from title page (Safari, viewed February 27, 2018)
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    Mastering the faster web with PHP, MySQL and JavaScript : develop state-of-the-art web applications using the latest web technologies (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788397711 , 1788397711
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: MySQL (Electronic resource) ; Web site development ; PHP (Computer program language) ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Make web applications run faster by using advanced PHP, SQL and JavaScript techniques About This Book Use a customized PHP stack to create efficient data-driven web applications Ensure seamless implementation of a JavaScript & HTML 5 CSS based frontend and PHP based backend. Learn about problem identification, best strategies, and UI design patterns as well to build a clean, fast web application Who This Book Is For The audience for this book would be PHP developers who have some basic knowledge of PHP programming and Web technologies. JavaScript programming knowledge is not necessary. What You Will Learn Install, confgure, and use profling and benchmarking testing tools Understand how to recognize optimizable data structures and functions to effectively optimize a PHP7 application Diagnose bad SQL query performance and discover ways to optimize it Grasp modern SQL techniques to optimize complex SQL queries Identify and simplify overly complex JavaScript code Explore and implement UI design principles that effectively enhance the performance Combine web technologies to boost web server performance In Detail This book will get you started with the latest benchmarking, profiling and monitoring tools for PHP, MySQL and JavaScript using Docker-based technologies. From optimizing PHP 7 code to learning asynchronous programming, from implementing Modern SQL solutions to discovering Functional JavaScript techniques, this book covers all the latest developments in Faster Web technologies. You will not only learn to determine the best optimization strategies, but also how to implement them. Along the way, you will learn how to profile your PHP scripts with Blackfire.io, monitor your Web applications, measure database performance, optimize SQL queries, explore Functional JavaScript, boost Web server performance in general and optimize applications when there is nothing left to optimize by going beyond performance. After reading this book, you will know how to boost the performance of any Web application and make it part of what has come to be known as the Faster Web. Style and approach The book has a step by step practical approach to developing highly efficient Web applications, with many practical and useful code snippets.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed July 5, 2018)
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  • 40
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    Vuex quick start guide : Centralized State Management for your Vue.js applications (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788991544 , 1788991540
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Application software Development ; JavaScript (Computer program language) ; Web applications
    Note: Description based on online resource; title from title page (Safari, viewed June 1, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788999939/?ar
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  • 41
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    Data analysis with Python : a modern approach (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789958195 , 1789958199
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Expert insight
    Keywords: Python (Computer program language) ; Machine learning ; Artificial intelligence ; Electronic data processing ; Electronic books ; Electronic books ; local
    Abstract: Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis. Key Features Bridge your data analysis with the power of programming, complex algorithms, and AI Use Python and its extensive libraries to power your way to new levels of data insight Work with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time series Explore this modern approach across with key industry case studies and hands-on projects Book Description Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you're likely to meet in today. The first of these is an image recognition application with TensorFlow ? embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence. What you will learn A new toolset that has been carefully crafted to meet for your data analysis challenges Full and detailed case studies of the toolset across several of today's key industry contexts Become super productive with a new toolset across Python and Jupyter Notebook Look into the future of data science an...
    Note: Includes bibliographical references and index. - Description based on online resource; title from cover (Safari, viewed February 26, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789950069/?ar
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  • 42
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    Vue.js 2 design patterns and best practices : build enterprise-ready, modular Vue.js applications with Vuex and Nuxt (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788831017 , 1788831012
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Web applications ; Programming ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Become an expert Vue developer by understanding the design patterns and component architecture of Vue.js to write clean and maintainable code. About This Book Craft highly modular applications by exploring the design patterns and component architecture of Vue.js Enforce a Flux-like application architecture in your Vue.js applications with Vuex Easy-to-follow examples that can be used to create reusable code and extensible designs Who This Book Is For This book targets Vue Developers who care about framework design principles and utilize commonly found design patterns in developing web applications. What You Will Learn Understand the theory and patterns of Vue.js Build scalable and modular Vue.js applications Take advantage of Vuex for reactive state management. Create Single Page Applications with vue-router. Use Nuxt for FAST server side rendered Vue applications. Convert your application to a Progressive Web App (PWA) and add ServiceWorkers, offline support, and more Build your app with Vue.js by following up with best practices and explore the common anti-patterns to avoid In Detail The book starts by comparing Vue.js with other frameworks and setting up the development environment for your application, and gradually move on to writing and styling clean, maintainable, and reusable components that can be used across your application. Further on, you'll look at common UI patterns, Vue form submission, and various modifiers such as lazy binding, number typecasting, and string trimming to create better UIs. You will also explore best practices for integrating HTTP into Vue.js applications to create an application with dynamic data. Routing is a vitally important part of any SPA, so you will focus on the Vue router and explore routing a user between multiple pages. Next, you'll also explore state management with Vuex, write testable code for your application, and create performant, server-side rendered applications with Nuxt. Towards the end, we'll look at common antipatterns to avoid, to save you from a lot of trial and error and development headaches. By the end of this book, you'll be well on your way to becoming an expert Vue developer who can leverage design patterns to efficiently architect the design of your application and write clean and maintainable code. Style and approach This easy-to-follow practical guide will help you develop efficient Vue.js apps by following best practices and using common design patterns. Downloading the exampl...
    Note: Description based on online resource; title from title page (viewed April 2, 2018)
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    Learning Three.js : programming 3D animations and visualizations for the web with HTML5 and WebGL (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788835978 , 1788835972
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: JavaScript (Computer program language) ; WebGL (Computer program language) ; Three-dimensional modeling ; Computer graphics ; Electronic books ; Electronic books ; local
    Abstract: Create and animate stunning 3D browser based graphics with Three.js JavaScript library Key Features Enhance your 3D graphics with light sources, shadows, advanced materials, and textures Load models from external sources, and visualize and animate them directly from JavaScript Create your own custom WebGL shader and explore the postprocessing feature of Three.js Book Description WebGL makes it possible to create 3D graphics in the browser without having to use plugins such as Flash and Java. Programming WebGL, however, is difficult and complex. With Three.js, it is possible to create stunning 3D graphics in an intuitive manner using JavaScript, without having to learn WebGL. With this book, you'll learn how to create and animate beautiful looking 3D scenes directly in your browser-utilizing the full potential of WebGL and modern browsers. It starts with the basic concepts and building blocks used in Three.js. From there on, it will expand on these subjects using extensive examples and code samples. You will learn to create, or load, from externally created models, realistic looking 3D objects using materials and textures. You'll find out how to easily control the camera using the Three.js built-in in camera controls, which will enable you to fly or walk around the 3D scene you created. You will then use the HTML5 video and canvas elements as a material for your 3D objects and to animate your models. Finally, you will learn to use morph and skeleton-based animation, and even how to add physics, such as gravity and collision detection, to your scene. After reading this book, you'll know everything that is required to create 3D animated graphics using Three.js. What you will learn Work with the different types of materials in Three.js and see how they interact with your 3D objects and the rest of the environment Implement the different camera controls provided by Three.js to effortlessly navigate around your 3D scene Work with vertices directly to create snow, rain, and galaxy-like effects Import and animate models from external formats, such as OBJ, STL, and COLLADA Create and run animations using morph targets and bones animations Explore advanced textures on materials to create realistic looking 3D objects by using bump maps, normal maps, specular maps, and light maps Interact directly with WebGL by creating custom vertex and fragment shaders Who this book is for The ideal target audience for this book would be JavaScript developers who who wa...
    Note: Description based on online resource; title from title page (Safari, viewed October 4, 2018)
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    Mastering TensorFlow 1.x : advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788297004 , 1788297008
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Build, scale, and deploy deep neural network models using the star libraries in Python About This Book Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras Build, deploy, and scale end-to-end deep neural network models in a production environment Learn to deploy TensorFlow on mobile, and distributed TensorFlow on GPU, Clusters, and Kubernetes Who This Book Is For This book is for data scientists, machine learning engineers, artificial intelligence engineers, and for all TensorFlow users who wish to upgrade their TensorFlow knowledge and work on various machine learning and deep learning problems. If you are looking for an easy-to-follow guide that underlines the intricacies and complex use cases of machine learning, you will find this book extremely useful. Some basic understanding of TensorFlow is required to get the most out of the book. What You Will Learn Master advanced concepts of deep learning such as transfer learning, reinforcement learning, generative models and more, using TensorFlow and Keras Perform supervised (classification and regression) and unsupervised (clustering) learning to solve machine learning tasks Build end-to-end deep learning (CNN, RNN, and Autoencoders) models with TensorFlow Scale and deploy production models with distributed and high-performance computing on GPU and clusters Build TensorFlow models to work with multilayer perceptrons using Keras, TFLearn, and R Learn the functionalities of smart apps by building and deploying TensorFlow models on iOS and Android devices Supercharge TensorFlow with distributed training and deployment on Kubernetes and TensorFlow Clusters In Detail TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs. This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim, Pretty Tensor, and Sonnet. Leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Throughout the book, you will obtain hands-on experience with varied datasets, such as MNIST, CIFAR-10, PTB, text8, and COCO-Images. You will learn the advanced features of TensorFlow1.x, such as distributed TensorFlow ...
    Note: Description based on online resource; title from title page (Safari, viewed February 16, 2018)
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    Artificial intelligence and machine learning fundamentals (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789809206 , 1789809207
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Artificial intelligence ; Neural networks (Computer science) ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Create AI applications in Python and lay the foundations for your career in data science Key Features Practical examples that explain key machine learning algorithms Explore neural networks in detail with interesting examples Master core AI concepts with engaging activities Book Description Machine learning and neural networks are pillars on which you can build intelligent applications. Artificial Intelligence and Machine Learning Fundamentals begins by introducing you to Python and discussing AI search algorithms. You will cover in-depth mathematical topics, such as regression and classification, illustrated by Python examples. As you make your way through the book, you will progress to advanced AI techniques and concepts, and work on real-life datasets to form decision trees and clusters. You will be introduced to neural networks, a powerful tool based on Moore's law. By the end of this book, you will be confident when it comes to building your own AI applications with your newly acquired skills! What you will learn Understand the importance, principles, and fields of AI Implement basic artificial intelligence concepts with Python Apply regression and classification concepts to real-world problems Perform predictive analysis using decision trees and random forests Carry out clustering using the k-means and mean shift algorithms Understand the fundamentals of deep learning via practical examples Who this book is for Artificial Intelligence and Machine Learning Fundamentals is for software developers and data scientists who want to enrich their projects with machine learning. You do not need any prior experience in AI. However, it's recommended that you have knowledge of high school-level mathematics and at least one programming language (preferably Python).
    Note: Description based on online resource; title from copyright page (Safari, viewed February 11, 2019)
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  • 46
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    Deep learning with PyTorch quick start guide : learn to train and deploy neural network models in Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789539738 , 1789539730
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Machine learning ; Python (Computer program language) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing. Key Features Clear and concise explanations Gives important insights into deep learning models Practical demonstration of key concepts Book Description PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. What you will learn Set up the deep learning environment using the PyTorch library Learn to build a deep learning model for image classification Use a convolutional neural network for transfer learning Understand to use PyTorch for natural language processing Use a recurrent neural network to classify text Understand how to optimize PyTorch in multiprocessor and distributed environments Train, optimize, and deploy your neural networks for maximum accuracy and performance Learn to deploy production-ready models Who this book is for Developers and Data Scientist familiar with Machine Learning but new to deep learning, or existing practitioners of deep learning who would like to use PyTorch to train their deep learning models will find this book to be useful. Having knowledge of Python programming will be an added advantage, while previous exposure to PyTorch is not needed.
    Note: Description based on online resource; title from title page (viewed February 15, 2019)
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    Server side development with Node.js and Koa.js quick start guide : build robust and scalable web applications with modern JavaScript techniques (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789343663 , 1789343666
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Node.js ; JavaScript (Computer program language) ; Application software ; Development ; Web applications ; Electronic books ; Electronic books ; local
    Abstract: Build real-world robust web applications and APIs using the modern and expressive Koa Node.js framework. Key Features Get up and running with Koa.js and leverage its power with node.js Get the most out of Koa Async functions and generators Create real time dynamic serverside apps efficiently with Koa.js Book Description Every developer wants to build modular and scalable web applications. Modern versions of JavaScript have made this possible in Node.js, and Koa is a Node.js framework that makes it easy. This book is the ideal introduction for JavaScript developers who want to create scalable server side applications using Node.js and Koa.js. The book shows you how Koa can be used to start projects from scratch, register custom and existing middleware, read requests, and send responses to users. We will explore the core concepts in Koa, such as error handling, logging, and request and response handling. We will dive into new concepts in JavaScript development, and see how paradigms such as async/await help with modern Node.js application development. By the end of this book, you will be building robust web applications in Koa using modern development paradigms and techniques of Node.js development. What you will learn Create a simple server in Node.js and Koa Work with custom middleware in Koa Handle errors in Koa Create routes, handle requests, and send responses from APIs Build views and use templates in Koa Authenticate your application and structure it properly in Koa Who this book is for This book is for serverside developers and JavaScript developers who want to use Koa.js and Node.js to create fast and real time back end applications.
    Note: Description based on online resource; title from title page (Safari, viewed February 6, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789345391/?ar
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  • 48
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    Hands-on robotics with JavaScript : build robotic projects using Johnny-Five and control hardware with JavaScript and Raspberry Pi (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789346732 , 1789346738
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Robots ; Programming ; Personal robotics ; Robots ; Control systems ; Raspberry Pi (Computer) ; Electronic books ; Electronic books ; local
    Abstract: Leverage Raspberry Pi 3 and different JavaScript platforms to build exciting Robotics projects Key Features Build robots that light up and make noise Learn to work with Raspberry Pi 3 and JavaScript Connect your Johnny-Five projects to external APIs and create your own IoT Book Description There has been a rapid increase in the use of JavaScript in hardware and embedded device programming. JavaScript has an effective set of frameworks and libraries that support the robotics ecosystem. Hands-On Robotics with JavaScript starts with setting up an environment to program robots in JavaScript. Then, you will dive into building basic-level projects such as a line-following robot. You will walk through a series of projects that will teach you about the Johnny-Five library, and develop your skills with each project. As you make your way through the chapters, you'll work on creating a blinking LED, before moving on to sensors and other more advanced concepts. You will then progress to building an advanced-level AI-enabled robot, connect their NodeBots to the internet, create a NodeBots Swarm, and explore MQTT. By the end of this book, you will have gained hands-on experience in building robots using JavaScript What you will learn Install and run Node.js and Johnny-Five on Raspberry Pi Assemble, code, and run an LED project Leverage JavaScript libraries to build exciting robots Use sensors to collect data from the world around you Employ servos and motors to make your project move Add internet capabilities to your Johnny-Five project Who this book is for Hands-On Robotics with JavaScript is for individuals who have prior experience with Raspberry Pi 3 and like to write sketches in JavaScript. Basic knowledge of JavaScript and Node.js will help you get the most out of this book.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed October 1, 2018)
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    Hands-on design patterns with React Native : proven techniques and patterns for efficient native mobile development with JavaScript (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788999540 , 1788999541
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Application software ; Development ; Mobile apps ; Web site development ; Software patterns ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn how to write cross platform React Native code by using effective design patterns in the JavaScript world. Get to know industry standard patterns as well as situational patterns. Decouple your application with these set of ?Idea patterns?. Key Features Mobile development in React Native should be done in a reusable way. Learn how to build scalable applications using JavaScript patterns that are battle tested. Try effective techniques on your own using over 80 standalone examples. Book Description React Native helps developers reuse code across different mobile platforms like iOS and Android. This book will show you effective design patterns in the React Native world and will make you ready for professional development in big teams. The book will focus only on the patterns that are relevant to JavaScript, ECMAScript, React and React Native. However, you can successfully transfer a lot of the skills and techniques to other languages. I call them ?Idea patterns?. This book will start with the most standard development patterns in React like component building patterns, styling patterns in React Native and then extend these patterns to your mobile application using real world practical examples. Each chapter comes with full, separate source code of applications that you can build and run on your phone. The book is also diving into architectural patterns. Especially how to adapt MVC to React environment. You will learn Flux architecture and how Redux is implementing it. Each approach will be presented with its pros and cons. You will learn how to work with external data sources using libraries like Redux thunk and Redux Saga. The end goal is the ability to recognize the best solution for a given problem for your next mobile application. What you will learn Explore the design Patterns in React Native Learn the best practices for React Native development Explore common React patterns that are highly used within React Native development Learn to decouple components and use dependency injection in your applications Explore the best ways of fetching data from the backend systems Learn the styling patterns and how to implement custom mobile designs Explore the best ways to organize your application code in big codebases Who this book is for The ideal target audience for this book are people eager to learn React Native design patterns who already know the basics of JavaScript. We can assume that the target audience already knows how to write Hello Wo...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed October 22, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788994460/?ar
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  • 50
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    Hands-on intelligent agents with OpenAI Gym : a step-by-step guide to develop AI agents using deep reinforcement learning (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788835138 , 1788835131
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Machine learning ; Reinforcement learning ; Electronic books ; Electronic books ; local
    Abstract: Implement intelligent agents using PyTorch to solve classic AI problems, play console games like Atari, and perform tasks such as autonomous driving using the CARLA driving simulator Key Features Explore the OpenAI Gym toolkit and interface to use over 700 learning tasks Implement agents to solve simple to complex AI problems Study learning environments and discover how to create your own Book Description Many real-world problems can be broken down into tasks that require a series of decisions to be made or actions to be taken. The ability to solve such tasks without a machine being programmed requires a machine to be artificially intelligent and capable of learning to adapt. This book is an easy-to-follow guide to implementing learning algorithms for machine software agents in order to solve discrete or continuous sequential decision making and control tasks. Hands-On Intelligent Agents with OpenAI Gym takes you through the process of building intelligent agent algorithms using deep reinforcement learning starting from the implementation of the building blocks for configuring, training, logging, visualizing, testing, and monitoring the agent. You will walk through the process of building intelligent agents from scratch to perform a variety of tasks. In the closing chapters, the book provides an overview of the latest learning environments and learning algorithms, along with pointers to more resources that will help you take your deep reinforcement learning skills to the next level. What you will learn Explore intelligent agents and learning environments Understand the basics of RL and deep RL Get started with OpenAI Gym and PyTorch for deep reinforcement learning Discover deep Q learning agents to solve discrete optimal control tasks Create custom learning environments for real-world problems Apply a deep actor-critic agent to drive a car autonomously in CARLA Use the latest learning environments and algorithms to upgrade your intelligent agent development skills Who this book is for If you're a student, game/machine learning developer, or AI enthusiast looking to get started with building intelligent agents and algorithms to solve a variety of problems with the OpenAI Gym interface, this book is for you. You will also find this book useful if you want to learn how to build deep reinforcement learning-based agents to solve problems in your domain of interest. Though the book covers all the basic concepts that you need to know, some working kn...
    Note: Description based on online resource; title from title page (Safari, viewed August 27, 2018)
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    ECMAScript cookbook : over 70 recipes to help you learn the new ECMAScript (ES6/ES8) features and solve common JavaScript problems (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788625630 , 1788625633
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Application software ; Design ; Electronic books ; Electronic books ; local
    Abstract: Become a better web programmer by writing efficient and modular code using ES6 and ES8 About This Book Learn to write asynchronous code and improve the readability of your web applications Explore advanced concepts such as closures, Proxy, generators, Promise, async functions, and Atomics Use different design patterns to create structures to solve common organizational and processing issues Who This Book Is For If you're a web developer with a basic understanding of JavaScript and wish to learn the latest features of ECMAScript for developing efficient web applications, this book is for you. What You Will Learn Organize JavaScript programs across multiple files, using ES modules Create and work with promises using the Promise object and methods Compose async functions to propagate and handle errors Solve organizational and processing issues with structures using design patterns Use classes to encapsulate and share behavior Orchestrate parallel programs using WebWorkers, SharedMemory, and Atomics Use and extend Map, Set, and Symbol to work with user-defined classes and simulate data types Explore new array methods to avoid looping with arrays and other collections In Detail ECMAScript Cookbook follows a modular approach with independent recipes covering different feature sets and specifications of ECMAScript to help you become an efficient programmer. This book starts off with organizing your JavaScript applications as well as delivering those applications to modem and legacy systems. You will get acquainted with features of ECMAScript 8 such as async, SharedArrayBuffers, and Atomic operations that enhance asynchronous and parallel operations. In addition to this, this book will introduce you to SharedArrayBuffers, which allow web workers to share data directly, and Atomic operations, which help coordinate behavior across the threads. You will also work with OOP and Collections, followed by new functions and methods on the built-in Object and Array types that make common operations more manageable and less error-prone. You will then see how to easily build more sophisticated and expressive program structures with classes and inheritance. In the end, we will cover Sets, Maps, and Symbols, which are the new types introduced in ECMAScript 6 to add new behaviors and allow you to create simple and powerful modules. By the end of the book, you will be able to produce more efficient, expressive, and simpler programs using the new features of ECMAScrip...
    Note: Description based on online resource; title from title page (Safari, viewed May 3, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788628174/?ar
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    JavaScript cloud native development cookbook : deliver serverless cloud-native solutions on AWS, Azure, and GCP (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788475372 , 1788475372
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Application software ; Development ; Cloud computing ; Electronic books ; Electronic books ; local
    Abstract: Master over 60 recipes to help you deliver completely scalable and serverless cloud-native applications Key Features Develop global scale and event-driven autonomous services Continuously deploy, test, observe, and optimize your services Practical Node.js recipes for serverless cloud-native development Book Description Cloud-native development is a modern approach to building and running applications that leverages the merits of the cloud computing model. With cloud-native development, teams can deliver faster and in a more lean and agile manner as compared to traditional approaches. This recipe-based guide provides quick solutions for your cloud-native applications. Beginning with a brief introduction, JavaScript Cloud-Native Development Cookbook guides you in building and deploying serverless, event-driven, cloud-native microservices on AWS with Node.js. You'll then move on to the fundamental patterns of developing autonomous cloud-native services and understand the tools and techniques involved in creating globally scalable, highly available, and resilient cloud-native applications. The book also covers multi-regional deployments and leveraging the edge of the cloud to maximize responsiveness, resilience, and elasticity. In the latter chapters you'll explore techniques for building fully automated, continuous deployment pipelines and gain insights into polyglot cloud-native development on popular cloud platforms such as Azure and Google Cloud Platform (GCP). By the end of the book, you'll be able to apply these skills to build powerful cloud-native solutions. What you will learn Implement patterns such as Event Streaming, CQRS, and Event Sourcing Deploy multi-regional, multi-master solutions Secure your cloud-native services with OAuth and OpenID Connect Create a robust cloud-native continuous deployment pipeline Run services on AWS, Azure, and GCP Implement autonomous services to limit the impact of failures Who this book is for If you want to develop powerful serverless, cloud-native solutions, this book is for you. You are expected to have basic knowledge of concepts of microservices and hands-on experience with Node.js to understand the recipes in this book.
    Note: Description based on online resource; title from title page (Safari, viewed November 2, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788470414/?ar
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    Ethereum smart contract development : build blockchain-based decentralized applications using solidity (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788472623 , 1788472624
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Ethereum (Distributed computing platform) ; Blockchains (Databases) ; Distributed databases ; Electronic data processing Distributed processing ; JavaScript (Computer program language)
    Note: Description based on online resource; title from title page (Safari, viewed March 13, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788473040/?ar
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    Advanced deep learning with Keras : apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788624534 , 178862453X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Machine learning ; Python (Computer program language) ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: A comprehensive guide to advanced deep learning techniques, including Autoencoders, GANs, VAEs, and Deep Reinforcement Learning, that drive today's most impressive AI results Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement Deep Neural Networks, Autoencoders, GANs, VAEs, and Deep Reinforcement Learning A wide study of GANs, including Improved GANs, Cross-Domain GANs and Disentangled Representation GANs Book Description Recent developments in deep learning, including GANs, Variational Autoencoders, and Deep Reinforcement Learning, are creating impressive AI results in our news headlines - such as AlphaGo Zero beating world chess champions, and generative AI that can create art paintings that sell for over $400k because they are so human-like. Advanced Deep Learning with Keras is a comprehensive guide to the advanced deep learning techniques available today, so you can create your own cutting-edge AI. Using Keras as an open-source deep learning library, you'll find hands-on projects throughout that show you how to create more effective AI with the latest techniques. The journey begins with an overview of MLPs, CNNs, and RNNs, which are the building blocks for the more advanced techniques in the book. You'll learn how to implement deep learning models with Keras and Tensorflow, and move forwards to advanced techniques, as you explore deep neural network architectures, including ResNet and DenseNet, and how to create Autoencoders. You then learn all about Generative Adversarial Networks (GANs), and how they can open new levels of AI performance. Variational AutoEncoders (VAEs) are implemented, and you'll see how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans - a major stride forward for modern AI. To complete this set of advanced techniques, you'll learn how to implement Deep Reinforcement Learning (DRL) such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI. What you will learn Cutting-edge techniques in human-like AI performance Implement advanced deep learning models using Keras The building blocks for advanced techniques - MLPs, CNNs, and RNNs Deep neural networks ? ResNet and DenseNet Autoencoders and Variational AutoEncoders (VAEs) Generative Adversarial Networks (GANs) and creative AI techniques Disentangled Representation GANs, and Cross-Domain GANs Deep Reinforcement Learning (DRL) meth...
    Note: "Expert insight.". - Includes bibliographical references and index. - Description based on online resource; title from cover (Safari, viewed December 10, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788629416/?ar
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    TensorFlow deep learning projects : 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788398381 , 1788398386
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios About This Book Build efficient deep learning pipelines using the popular Tensorflow framework Train neural networks such as ConvNets, generative models, and LSTMs Includes projects related to Computer Vision, stock prediction, chatbots and more Who This Book Is For This book is for data scientists, machine learning developers as well as deep learning practitioners, who want to build interesting deep learning projects that leverage the power of Tensorflow. Some understanding of machine learning and deep learning, and familiarity with the TensorFlow framework is all you need to get started with this book. What You Will Learn Set up the TensorFlow environment for deep learning Construct your own ConvNets for effective image processing Use LSTMs for image caption generation Forecast stock prediction accurately with an LSTM architecture Learn what semantic matching is by detecting duplicate Quora questions Set up an AWS instance with TensorFlow to train GANs Train and set up a chatbot to understand and interpret human input Build an AI capable of playing a video game by itself ?and win it! In Detail TensorFlow is one of the most popular frameworks used for machine learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with very high accuracy. This book is your guide to master deep learning with TensorFlow with the help of 10 real-world projects. TensorFlow Deep Learning Projects starts with setting up the right TensorFlow environment for deep learning. Learn to train different types of deep learning models using TensorFlow, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, and Generative Adversarial Networks. While doing so, you will build end-to-end deep learning solutions to tackle different real-world problems in image processing, recommendation systems, stock prediction, and building chatbots, to name a few. You will also develop systems that perform machine translation, and use reinforcement learning techniques to play games. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow, and will be able to build and train your own deep learning models with TensorFlow confidently. Style and approach This book contains 10 unique, end-to-end projects covering all aspects of ...
    Note: Description based on online resource; title from title page (Safari, viewed April 19, 2018)
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    Hands-on TypeScript for C# and . NET Core developers : transition from C# to TypeScript 3.1 and build applications with ASP.NET Core 2 (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789133325 , 1789133327
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: TypeScript (Computer program language) ; Application software ; Development ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Discover how TypeScript allows you to build modern client-rich applications, thanks to its object-oriented capabilities and third-party tools like Angular and Web APIs Key Features Make a seamless transition to using TypeScript 3.1 in your development stack Work with TypeScript 3.1 in your ASP.NET Core projects to build rich applications that are easy to maintain Build, test, and integrate your own TypeScript library in real-world projects Book Description Writing clean, object-oriented code in JavaScript gets trickier and complex as the size of the project grows. This is where Typescript comes into the picture; it lets you write pure object-oriented code with ease, giving it the upper hand over JavaScript. This book introduces you to basic TypeScript concepts by gradually modifying standard JavaScript code, which makes learning TypeScript easy for C# ASP.NET developers. As you progress through the chapters, you'll cover object programming concepts, such as classes, interfaces, and generics, and understand how they are related to, and similar in, both ES6 and C#. You will also learn how to use bundlers like WebPack to package your code and other resources. The book explains all concepts using practical examples of ASP.NET Core projects, and reusable TypeScript libraries. Finally, you'll explore the features that TypeScript inherits from either ES6 or C#, or both of them, such as Symbols, Iterables, Promises, and Decorators. By the end of the book, you'll be able to apply all TypeScript concepts to understand the Angular framework better, and you'll have become comfortable with the way in which modules, components, and services are defined and used in Angular. You'll also have gained a good understanding of all the features included in the Angular/ASP.NET Core Visual Studio project template. What you will learn Organize, test, and package large TypeScript code base Add TypeScript to projects using TypeScript declaration files Perform DOM manipulation with TypeScript Develop Angular projects with the Visual Studio Angular project template Define and use inheritance, abstract classes, and methods Leverage TypeScript-type compatibility rules Use WebPack to bundle JavaScript and other resources such as CSS to improve performance Build custom directives and attributes, and learn about animations Who this book is for If you're a C# or .NET developer looking for an easy accessible way of learning TypeScript, this book is for you.
    Note: Description based on online resource; title from title page (viewed January 9, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789130287/?ar
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    Hands-on computer vision with Julia : build complex applications with advanced Julia packages for image processing, neural networks, and artificial intelligence (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788999236 , 1788999231
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Julia (Computer program language) ; Information visualization ; Neural networks (Computer science) ; Application software ; Development ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Explore the various packages in Julia that support image processing and build neural networks for video processing and object tracking. About This Book Build a full-fledged image processing application using JuliaImages Perform basic to advanced image and video stream processing with Julia's APIs Understand and optimize various features of OpenCV with easy examples Who This Book Is For Hands-On Computer Vision with Julia is for Julia developers who are interested in learning how to perform image processing and want to explore the field of computer vision. Basic knowledge of Julia will help you understand the concepts more effectively. What You Will Learn Analyze image metadata and identify critical data using JuliaImages Apply filters and improve image quality and color schemes Extract 2D features for image comparison using JuliaFeatures Cluster and classify images with KNN/SVM machine learning algorithms Recognize text in an image using the Tesseract library Use OpenCV to recognize specific objects or faces in images and videos Build neural network and classify images with MXNet In Detail Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it's easy to use and lets you write easy-to-compile and efficient machine code. This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. You'll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you'll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned. By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease. Style and approach Readers will be taken through various packages that support image processing in Julia, ...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed August 8, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788998796/?ar
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    Hands-on machine learning with JavaScript : solve complex computational web problems using machine learning (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788990301 , 1788990307
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Machine learning ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: A definitive guide to creating an intelligent web application with the best of machine learning and JavaScript About This Book Solve complex computational problems in browser with JavaScript Teach your browser how to learn from rules using the power of machine learning Understand discoveries on web interface and API in machine learning Who This Book Is For This book is for you if you are a JavaScript developer who wants to implement machine learning to make applications smarter, gain insightful information from the data, and enter the field of machine learning without switching to another language. Working knowledge of JavaScript language is expected to get the most out of the book. What You Will Learn Get an overview of state-of-the-art machine learning Understand the pre-processing of data handling, cleaning, and preparation Learn Mining and Pattern Extraction with JavaScript Build your own model for classification, clustering, and prediction Identify the most appropriate model for each type of problem Apply machine learning techniques to real-world applications Learn how JavaScript can be a powerful language for machine learning In Detail In over 20 years of existence, JavaScript has been pushing beyond the boundaries of web evolution with proven existence on servers, embedded devices, Smart TVs, IoT, Smart Cars, and more. Today, with the added advantage of machine learning research and support for JS libraries, JavaScript makes your browsers smarter than ever with the ability to learn patterns and reproduce them to become a part of innovative products and applications. Hands-on Machine Learning with JavaScript presents various avenues of machine learning in a practical and objective way, and helps implement them using the JavaScript language. Predicting behaviors, analyzing feelings, grouping data, and building neural models are some of the skills you will build from this book. You will learn how to train your machine learning models and work with different kinds of data. During this journey, you will come across use cases such as face detection, spam filtering, recommendation systems, character recognition, and more. Moreover, you will learn how to work with deep neural networks and guide your applications to gain insights from data. By the end of this book, you'll have gained hands-on knowledge on evaluating and implementing the right model, along with choosing from different JS libraries, such as NaturalNode, brain, harthur, classifier,...
    Note: Description based on online resource; title from title page (Safari, viewed June 20, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788998246/?ar
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    Learn WebAssembly : build web applications with native performance using Wasm and C/C++ (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788995467 , 1788995465
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Web applications ; Application software ; Development ; JavaScript (Computer program language) ; C (Computer program language) ; C++ (Computer program language) ; Application program interfaces (Computer software) ; Electronic books ; Electronic books ; local
    Abstract: Create unbelievably fast, robust and secure web apps with Django Web Framework and Python 3.6 Key Features Generate WebAssembly modules from C and C++ using Emscripten and interact with these modules in the browser Learn how to use WebAssembly outside of the browser and load modules using Node.js Build a high-performance application using C and WebAssembly and port an existing C++ game to WebAssembly using Emscripten Book Description WebAssembly is a brand-new technology that represents a paradigm shift in web development. This book aims to teaches programmers how to leverage this technology to write high- performance applications that run in the browser. This book will introduces you to the powerful WebAssembly concepts of WebAssembly that willto help you write lean and powerful web applications with native performance. You will start with the evolution of web programming, the state of things today, and what can be done with the advent and release of WebAssembly. We take a look at the journey from JavaScript to asm.js to WebAssembly. We then move on to analyzinge the anatomy of a WebAssembly module and the relationship between the binary and text formats, along with the corresponding JavaScript API. Further on, weyou'll implement all the techniques you've learned by to building a high-performance application using C and WebAssembly, and then port an existing game written in C++ to WebAssembly using Emscripten. By the end of this book, you would will be well-equipped to create high-performance applications and games for the web using WebAssembly. What you will learn Learn how WebAssembly came to be and its associated elements (text format, module, and JavaScript API) Create, load, and debug a WebAssembly module (editor and compiler/toolchain) Build a high-performance application using C and WebAssembly Extend WebAssembly's feature set using Emscripten by porting a game written in C++ Explore upcoming features of WebAssembly, Node.js integration, and alternative compilation methods Who this book is for If you are a web developer or C/C++ programmer keen to leverage the powerful technology of WebAssembly to build high-performance web applications, then this book is for you. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed October 29, 2018)
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    Internet of things with Raspberry Pi 3 : leverage the power of Raspberry Pi 3 and JavaScript to build exciting IoT projects (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788620659 , 1788620658
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Raspberry Pi (Computer) ; Programming ; Internet of things ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Unleash the power of the Raspberry Pi 3 board to create interesting IoT projects About This Book Learn how to interface various sensors and actuators with the Raspberry Pi 3 and send this data to the cloud. Explore the possibilities offered by the IoT by using the Raspberry Pi to upload measurements to Google Docs. A practical guide that will help you create a Raspberry Pi robot using IoT modules. Who This Book Is For If you're a developer or electronics engineer and are curious about the Internet of Things, then this is the book for you. With only a rudimentary understanding of electronics, the Raspberry Pi, or similar credit-card sized computers, and some programming experience, you will be taught to develop state-of-the-art solutions for the Internet of Things in an instant. What You Will Learn Understand the concept of IoT and get familiar with the features of Raspberry Pi Learn to integrate sensors and actuators with the Raspberry Pi Communicate with cloud and Raspberry using communication protocols such as HTTP and MQTT Build DIY projects using Raspberry Pi, JavaScript/node.js and cloud (AWS) Explore the best practices to ensure the security of your connected devices In Detail This book is designed to introduce you to IoT and Raspberry Pi 3. It will help you create interesting projects, such as setting up a weather station and measuring temperature and humidity using sensors; it will also show you how to send sensor data to cloud for visualization in real-time. Then we shift our focus to leveraging IoT for accomplishing complex tasks, such as facial recognition using the Raspberry Pi camera module, AWS Rekognition, and the AWS S3 service. Furthermore, you will master security aspects by building a security surveillance system to protect your premises from intruders using Raspberry Pi, a camera, motion sensors, and AWS Cloud. We'll also create a real-world project by building a Wi-Fi - controlled robot car with Raspberry Pi using a motor driver circuit, DC motor, and a web application. This book is a must-have as it provides a practical overview of IoT's existing architectures, communication protocols, and security threats at the software and hardware levels-security being the most important aspect of IoT. Style and approach Internet of Things with the Raspberry Pi 3 contains the tools needed to design, sense the environment, communicate over the Internet, and visualize the results. Downloading the example code for this book You can downl...
    Note: Description based on online resource; title from title page (Safari, viewed June 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788627405/?ar
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    Building machine learning systems with Python : explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788622226 , 1788622227
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Python (Computer program language) ; Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Get more from your data by creating practical machine learning systems with Python Key Features Develop your own Python-based machine learning system Discover how Python offers multiple algorithms for modern machine learning systems Explore key Python machine learning libraries to implement in your projects Book Description Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you'll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems. By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks. What you will learn Build a classification system that can be applied to text, images, and sound Employ Amazon Web Services (AWS) to run analysis on the cloud Solve problems related to regression using scikit-learn and TensorFlow Recommend products to users based on their past purchases Understand different ways to apply deep neural networks on structured data Address recent developments in the field of computer vision and reinforcement learning Who this book is for Building Machine Learning Systems with Python is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. You will use Python's machine learning capabilities to develop effective solutions. Prior knowledge of Python progr...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed August 27, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788623223/?ar
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    Learn Blockchain programming with JavaScript : build your very own Blockchain and decentralized network with JavaScript and Node.js (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789614848 , 1789614848
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Node.js ; Blockchains (Databases) ; Application program interfaces (Computer software) ; JavaScript (Computer program language) ; Electronic data processing ; Distributed processing ; Electronic books ; Electronic books ; local
    Abstract: Explore the essentials of blockchain technology with JavaScript to develop highly secure bitcoin-like applications Key Features Develop bitcoin and blockchain-based cryptocurrencies using JavaScript Create secure and high-performant blockchain networks Build custom APIs and decentralized networks to host blockchain applications Book Description Learn Blockchain Programming with JavaScript begins by giving you a clear understanding of what blockchain technology is. You'll then set up an environment to build your very own blockchain and you'll add various functionalities to it. By adding functionalities to your blockchain such as the ability to mine new blocks, create transactions, and secure your blockchain through a proof-of-work you'll gain an in-depth understanding of how blockchain technology functions. As you make your way through the chapters, you'll learn how to build an API server to interact with your blockchain and how to host your blockchain on a decentralized network. You'll also build a consensus algorithm and use it to verify data and keep the entire blockchain network synchronized. In the concluding chapters, you'll finish building your blockchain prototype and gain a thorough understanding of why blockchain technology is so secure and valuable. By the end of this book, you'll understand how decentralized blockchain networks function and why decentralization is such an important feature for securing a blockchain. What you will learn Gain an in-depth understanding of blockchain and the environment setup Create your very own decentralized blockchain network from scratch Build and test the various endpoints necessary to create a decentralized network Learn about proof-of-work and the hashing algorithm used to secure data Mine new blocks, create new transactions, and store the transactions in blocks Explore the consensus algorithm and use it to synchronize the blockchain network Who this book is for Learn Blockchain Programming with JavaScript is for JavaScript developers who wish to learn about blockchain programming or build their own blockchain using JavaScript frameworks.
    Note: Description based on online resource; title from title page (Safari, viewed February 4, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789618822/?ar
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    Beginning React : simplify your frontend development workflow and enhance the user experience of your applications with React (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789534924 , 1789534925
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Mobile apps ; Application software ; Development ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Take your web applications to a whole new level with efficient, component-based UIs that deliver cutting-edge interactivity and performance. Key Features Elaborately explains basics before introducing advanced topics Explains creating and managing the state of components across applications Implement over 15 practical activities and exercises across 11 topics to reinforce your learning Book Description Projects like Angular and React are rapidly changing how development teams build and deploy web applications to production. In this book, you'll learn the basics you need to get up and running with React and tackle real-world projects and challenges. It includes helpful guidance on how to consider key user requirements within the development process, and also shows you how to work with advanced concepts such as state management, data-binding, routing, and the popular component markup that is JSX. As you complete the included examples, you'll find yourself well-equipped to move onto a real-world personal or professional frontend project. What you will learn Understand how React works within a wider application stack Analyze how you can break down a standard interface into specific components Successfully create your own increasingly complex React components with HTML or JSX Correctly handle multiple user events and their impact on overall application state Understand the component lifecycle to optimize the UX of your application Configure routing to allow effortless, intuitive navigation through your components Who this book is for If you are a frontend developer who wants to create truly reactive user interfaces in JavaScript, then this is the book for you. For React, you'll need a solid foundation in the essentials of the JavaScript language, including new OOP features that were introduced in ES2015. An understanding of HTML and CSS is assumed, and a basic knowledge of Node.js will be useful in the context of managing a development workflow, but is not essential.
    Note: Description based on online resource; title from title page (Safari, viewed August 28, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789530520/?ar
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    Learning Microsoft Cognitive Services : use Cognitive Services APIs to add AI capabilities to your applications (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789803686 , 1789803683
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Microsoft Visual studio ; Application program interfaces (Computer software) ; Artificial intelligence ; Machine learning ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Build smarter applications with AI capabilities using Microsoft Cognitive Services APIs without much hassle Key Features Explore the Cognitive Services APIs for building machine learning applications Build applications with computer vision, speech recognition, and language processing capabilities Learn to implement human-like cognitive intelligence for your applications Book Description Microsoft Cognitive Services is a set of APIs for adding intelligence to your application and leverage the power of AI to solve any business problem using the cognitive capabilities. This book will be your practical guide to working with cognitive APIs developed by Microsoft and provided with the Azure platform to developers and businesses. You will learn to integrate the APIs with your applications in Visual Studio. The book introduces you to about 24 APIs including Emotion, Language, Vision, Speech, Knowledge, and Search among others. With the easy-to-follow examples you will be able to develop applications for image processing, speech recognition, text procession, and so on to enhance the capability of your applications to perform more human-like tasks. Going ahead, the book will help you work with the datasets that enable your applications to process various data in form of image, videos, and texts. By the end of the book, you will get confident to explore the Cognitive Services APIs for your applications and make them intelligent for deploying in businesses. What you will learn Identify a person through visual and audio inspection Reduce user effort by utilizing AI-like capabilities Understand how to analyze images and texts in different ways Analyze images using Vision APIs Add video analysis to applications using Vision APIs Utilize Search to find anything you want Analyze text to extract information and explore text structure Who this book is for Learning Microsoft Cognitive Services is for developers and machine learning enthusiasts who want to get started with building intelligent applications without much programming knowledge. Some prior knowledge of .NET and Visual Studio will help you undertake the tasks explained in this book.
    Note: Includes index. - Description based on online resource; title from cover (viewed November 6, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789800616/?ar
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    Hands-on artificial intelligence for search : building intelligent applications and perform enterprise searches (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789612479 , 1789612470
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Application software ; Development ; Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Make your searches more responsive and smarter by applying Artificial Intelligence to it Key Features Enter the world of Artificial Intelligence with solid concepts and real-world use cases Make your applications intelligent using AI in your day-to-day apps and become a smart developer Design and implement artificial intelligence in searches Book Description With the emergence of big data and modern technologies, AI has acquired a lot of relevance in many domains. The increase in demand for automation has generated many applications for AI in fields such as robotics, predictive analytics, finance, and more. In this book, you will understand what artificial intelligence is. It explains in detail basic search methods: Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search, which can be used to make intelligent decisions when the initial state, end state, and possible actions are known. Random solutions or greedy solutions can be found for such problems. But these are not optimal in either space or time and efficient approaches in time and space will be explored. We will also understand how to formulate a problem, which involves looking at it and identifying its initial state, goal state, and the actions that are possible in each state. We also need to understand the data structures involved while implementing these search algorithms as they form the basis of search exploration. Finally, we will look into what a heuristic is as this decides the quality of one sub-solution over another and helps you decide which step to take. What you will learn Understand the instances where searches can be used Understand the algorithms that can be used to make decisions more intelligent Formulate a problem by specifying its initial state, goal state, and actions Translate the concepts of the selected search algorithm into code Compare how basic search algorithms will perform for the application Implement algorithmic programming using code examples Who this book is for This book is for developers who are keen to get started with Artificial Intelligence and develop practical AI-based applications. Those developers who want to upgrade their normal applications to smart and intelligent versions will find this book useful. A basic knowledge and understanding of Python are assumed.
    Note: Description based on online resource; title from title page (Safari, viewed October 8, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789611151/?ar
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    Building RESTful web services with Java EE 8 : create modern RESTful web services with the Java EE 8 API (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789534269 , 1789534267
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Representational State Transfer (Software architecture) ; Web services ; Design ; Application program interfaces (Computer software) ; Electronic books ; Electronic books ; local
    Abstract: Learn the fundamentals of Java EE 8 APIs to build effective web services Key Features Design modern and stylish web services with Java EE APIs Secure your web services with JSON Web Tokens Explore the advanced concepts of RESTful web services and the JAX-RS API Book Description Java Enterprise Edition is one of the leading application programming platforms for enterprise Java development. With Java EE 8 finally released and the first application servers now available, it is time to take a closer look at how to develop modern and lightweight web services with the latest API additions and improvements. Building RESTful Web Services with Java EE 8 is a comprehensive guide that will show you how to develop state-of-the-art RESTful web services with the latest Java EE 8 APIs. You will begin with an overview of Java EE 8 and the latest API additions and improvements. You will then delve into the details of implementing synchronous RESTful web services and clients with JAX-RS. Next up, you will learn about the specifics of data binding and content marshalling using the JSON-B 1.0 and JSON-P 1.1 APIs. This book also guides you in leveraging the power of asynchronous APIs on the server and client side, and you will learn to use server-sent events (SSEs) for push communication. The final section covers advanced web service topics such as validation, JWT security, and diagnosability. By the end of this book, you will have implemented several working web services and have a thorough understanding of the Java EE 8 APIs required for lightweight web service development. What you will learn Dive into the latest Java EE 8 APIs relevant for developing web services Use the new JSON-B APIs for easy data binding Understand how JSON-P API can be used for flexible processing Implement synchronous and asynchronous JAX-RS clients Use server-sent events to implement server-side code Secure Java EE 8 web services with JSON Web Tokens Who this book is for If you're a Java developer who wants to learn how to implement web services using the latest Java EE 8 APIs, this book is for you. Though no prior knowledge of Java EE 8 is required, experience with a previous Java EE version will be beneficial.
    Note: Description based on online resource; title from title page (Safari, viewed August 29, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789532883/?ar
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    Architects of intelligence : the truth about AI from the people building it (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789131260 , 178913126X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Computer scientists ; Interviews ; Electronic books ; Electronic books ; local
    Abstract: Book Description How will AI evolve and what major innovations are on the horizon? What will its impact be on the job market, economy, and society? What is the path toward human-level machine intelligence? What should we be concerned about as artificial intelligence advances? Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community. Martin has wide-ranging conversations with twenty-three of the world's foremost researchers and entrepreneurs working in AI and robotics: Demis Hassabis (DeepMind), Ray Kurzweil (Google), Geoffrey Hinton (Univ. of Toronto and Google), Rodney Brooks (Rethink Robotics), Yann LeCun (Facebook) , Fei-Fei Li (Stanford and Google), Yoshua Bengio (Univ. of Montreal), Andrew Ng (AI Fund), Daphne Koller (Stanford), Stuart Russell (UC Berkeley), Nick Bostrom (Univ. of Oxford), Barbara Grosz (Harvard), David Ferrucci (Elemental Cognition), James Manyika (McKinsey), Judea Pearl (UCLA), Josh Tenenbaum (MIT), Rana el Kaliouby (Affectiva), Daniela Rus (MIT), Jeff Dean (Google), Cynthia Breazeal (MIT), Oren Etzioni (Allen Institute for AI), Gary Marcus (NYU), and Bryan Johnson (Kernel). Martin Ford is a prominent futurist, and author of Financial Times Business Book of the Year, Rise of the Robots. He speaks at conferences and companies around the world on what AI and automation might mean for the future.
    Note: Description based on online resource; title from cover (Safari, viewed January 23, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789131512/?ar
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    Intelligent mobile projects with TensorFlow : build 10+ artificial intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788628808 , 1788628802
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Mobile apps ; Application software ; Development ; Artificial intelligence ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Create Deep Learning and Reinforcement Learning apps for multiple platforms with TensorFlow About This Book Build TensorFlow-powered AI applications for mobile and embedded devices Learn modern AI topics such as computer vision, NLP, and deep reinforcement learning Get practical insights and exclusive working code not available in the TensorFlow documentation Who This Book Is For If you're an iOS/Android developer interested in building and retraining others' TensorFlow models and running them in your mobile apps, or if you're a TensorFlow developer and want to run your new and amazing TensorFlow models on mobile devices, this book is for you. You'll also benefit from this book if you're interested in TensorFlow Lite, Core ML, or TensorFlow on Raspberry Pi. What You Will Learn Classify images with transfer learning Detect objects and their locations Transform pictures with amazing art styles Understand simple speech commands Describe images in natural language Recognize drawing with Convolutional Neural Network and Long Short-Term Memory Predict stock price with Recurrent Neural Network in TensorFlow and Keras Generate and enhance images with generative adversarial networks Build AlphaZero-like mobile game app in TensorFlow and Keras Use TensorFlow Lite and Core ML on mobile Develop TensorFlow apps on Raspberry Pi that can move, see, listen, speak, and learn In Detail As a developer, you always need to keep an eye out and be ready for what will be trending soon, while also focusing on what's trending currently. So, what's better than learning about the integration of the best of both worlds, the present and the future? Artificial Intelligence (AI) is widely regarded as the next big thing after mobile, and Google's TensorFlow is the leading open source machine learning framework, the hottest branch of AI. This book covers more than 10 complete iOS, Android, and Raspberry Pi apps powered by TensorFlow and built from scratch, running all kinds of cool TensorFlow models offline on-device: from computer vision, speech and language processing to generative adversarial networks and AlphaZero-like deep reinforcement learning. You'll learn how to use or retrain existing TensorFlow models, build your own models, and develop intelligent mobile apps running those TensorFlow models. You'll learn how to quickly build such apps with step-by-step tutorials and how to avoid many pitfalls in the process with lots of hard-earned troubleshooting tips. Style and a...
    Note: Description based on online resource; title from title page (Safari, viewed June 15, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788834544/?ar
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    React cookbook : create dynamic web apps with React using Redux, Webpack, Node.js, and GraphQL (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785282591 , 178528259X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Application software ; Development ; JavaScript (Computer program language) ; Mobile apps ; Web site development ; Web sites ; Design ; Electronic books ; Electronic books ; local
    Abstract: Over 66 hands-on recipes that cover UI development, animations, component architecture, routing, databases, testing, and debugging with React Key Features Use essential hacks and simple techniques to solve React application development challenges Create native mobile applications for iOS and Android using React Native Learn to write robust tests for your applications using Jest and Enzyme Book Description Today's web demands efficient real-time applications and scalability. If you want to learn to build fast, efficient, and high-performing applications using React 16, this is the book for you. We plunge directly into the heart of all the most important React concepts for you to conquer. Along the way, you'll learn how to work with the latest ECMAScript features. You'll see the fundamentals of Redux and find out how to implement animations. Then, you'll learn how to create APIs with Node, Firebase, and GraphQL, and improve the performance of our application with Webpack 4.x. You'll find recipes on implementing server-side rendering, adding unit tests, and debugging. We also cover best practices to deploy a React application to production. Finally, you'll learn how to create native mobile applications for iOS and Android using React Native. By the end of the book, you'll be saved from a lot of trial and error and developmental headaches, and you'll be on the road to becoming a React expert. What you will learn Gain the ability to wield complex topics such as Webpack and server-side rendering Implement an API using Node.js, Firebase, and GraphQL Learn to maximize the performance of React applications Create a mobile application using React Native Deploy a React application on Digital Ocean Get to know the best practices when organizing and testing a large React application Who this book is for If you're a JavaScript developer who wants to build fast, efficient, scalable solutions, then you're in the right place. Knowledge of React will be an advantage but is not required. Experienced users of React will be able to improve their skills. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Description based on online resource; title from title page (Safari, viewed September 28, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781783980727/?ar
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    Artificial Intelligence for big data : complete guide to automating big data solutions using artificial intelligence techniques (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788476010 , 1788476018
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Big data ; Electronic books ; Electronic books ; local
    Abstract: Build next-generation Artificial Intelligence systems with Java About This Book Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Who This Book Is For This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus. What You Will Learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms In Detail In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. Style and approach An easy-to-follow, step-by-step guide to help you get to grips with real-world applications of Artificial Intelligence for big data using Java
    Note: Description based on online resource; title from title page (Safari, viewed June 29, 2018)
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    MERN quick start guide : build web applications with MongoDB, Express.js, React, and Node (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787280045 , 1787280047
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: MongoDB. ; Express.js (Electronic resource) ; Node.js ; Application software Development ; Web applications ; JavaScript (Computer program language)
    Note: Description based on online resource; title from title page (Safari, viewed June 27, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781787281080/?ar
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    React : cross-platform application development with React Native : build 4 real-world apps with React Native (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789139600 , 1789139600
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Mobile apps Development ; JavaScript (Computer program language) ; Application software Development
    Note: Description based on online resource; title from cover (Safari, viewed April 3, 2018). - "Rapid learning solution."
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781789136081/?ar
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    Unity 2017 AI game programming : leverage the power of artificial intelligence to program smart entities for your games (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788393294 , 1788393295
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition
    Parallel Title: Erscheint auch als
    Keywords: Unity (Electronic resource) ; Computer games Programming ; Artificial intelligence ; Three-dimensional display systems
    Note: Description based on online resource; title from title page (Safari, viewed February 28, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788477901/?ar
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    Learning JavaScript data structures and algorithms : write complex and powerful JavaScript code using the latest ECMAScript (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788624947 , 1788624947
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition
    Parallel Title: Erscheint auch als
    Keywords: JavaScript (Computer program language) ; Data structures (Computer science) ; Algorithms
    Note: Description based on online resource; title from title page (Safari, viewed May 31, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788623872/?ar
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    Google Cloud AI Services quick start guide : build intelligent applications with Google Cloud AI Services (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788996532 , 1788996534
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Google (Firm) ; Cloud computing ; Artificial intelligence ; Application software Development ; Application program interfaces (Computer software)
    Note: Description based on online resource; title from title page (Safari, viewed June 20, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788626613/?ar
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    Truffle quick start guide : learn the fundamentals of Ethereum development (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789136975 , 1789136970
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Application software Development ; Web site development ; JavaScript (Computer program language)
    Note: Description based on online resource; title from title page (Safari, viewed July 23, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781789132540/?ar
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    Advanced Node.js development : master Node.js by building real-world applications (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788394796 , 1788394798
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: JavaScript (Computer program language) ; Application software Development ; Web applications ; Web site development
    Note: Description based on online resource; title from title page (Safari, viewed May 3, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: https://learning.oreilly.com/library/view/-/9781788393935/?ar
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    Python advanced guide to artificial intelligence : expert machine learning systems and intelligent agents using Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789951721 , 1789951720
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Artificial intelligence ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features Master supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and more Build, deploy, and scale end-to-end deep neural network models in a production environment Book Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: Mastering Machine Learning Algorithms by Giuseppe Bonaccorso Mastering TensorFlow 1.x by Armando Fandango Deep Learning for Computer Vision by Rajalingappaa Shanmugamani What you will learn Explore how an ML model can be trained, optimized, and evaluated Work with Autoencoders and Generative Adversarial Networks Explore the most important Reinforcement Learning techniques Build end-to-end deep learning (CNN, RNN, and Autoencoders) models Who this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some un...
    Note: Description based on online resource; title from cover (Safari, viewed February 22, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789957211/?ar
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    Hands-on deep learning for images with TensorFlow : build intelligent computer vision applications using TensorFlow and Keras (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789532517 , 1789532515
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Computer vision ; Artificial intelligence ; Image processing ; Electronic books ; Electronic books ; local
    Abstract: Explore TensorFlow's capabilities to perform efficient deep learning on images Key Features Discover image processing for machine vision Build an effective image classification system using the power of CNNs Leverage TensorFlow's capabilities to perform efficient deep learning Book Description TensorFlow is Google's popular offering for machine learning and deep learning, quickly becoming a favorite tool for performing fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations of real-world projects, teaching you how to leverage TensorFlow's capabilities to perform efficient image processing using the power of deep learning. With the help of this book, you will get to grips with the different paradigms of performing deep learning such as deep neural nets and convolutional neural networks, followed by understanding how they can be implemented using TensorFlow. By the end of this book, you will have mastered all the concepts of deep learning and their implementation with TensorFlow and Keras. What you will learn Build machine learning models particularly focused on the MNIST digits Work with Docker and Keras to build an image classifier Understand natural language models to process text and images Prepare your dataset for machine learning Create classical, convolutional, and deep neural networks Create a RESTful image classification server Who this book is for Hands-On Deep Learning for Images with TensorFlow is for you if you are an application developer, data scientist, or machine learning practitioner looking to integrate machine learning into application software and master deep learning by implementing practical projects in TensorFlow. Knowledge of Python programming and basics of deep learning are required to get the best out of this book.
    Note: Description based on online resource; title from title page (Safari, viewed September 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789538670/?ar
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  • 80
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    React Router quick start guide : routing in React applications made easy (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789532838 , 1789532833
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Application software ; Development ; Web applications ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn how you can implement routing in a React Web/Native application using React-Router library Key Features Create nested routes and complex workflows for your applications Learn Routing in server-side rendered applications and in Native mobile applications Understand how Redux bindings for React-Router works using the connected-react-router library Book Description React Router is the routing library for React, and it can be used in both React Web and React Native applications. This book is a simple way to get started with React Router and harness its full power for your applications. The book starts with an introduction to React Router and teaches you how to create your first route using the React component. You will then learn about configuring your routes, passing parameters, and creating nested routes. You will be introduced to various components in React-Router and learn different configuration options available for these components. You will then see how to use the Redirect and Switch components. For even greater flexibility, you will learn about BrowserRouter, HashRouter, NativeRouter, and StaticRouter. By the end of the book, you will have set up a project with React Router and make routing configuration work in a server-side rendered React application, a mobile application built with React Native and also understand how Redux and React-Router can be used in the same application. What you will learn Create your first Route using the Route component Protect routes from unauthorized access by using the redirect component Navigate to your defined route using Link and NavLink Configure BrowserRouter and HashRouter using various props Use StaticRouter for routing in server-side rendered React applications Implement routing in a React Native app using react-router-native Using connected-react-router library with React-Router for better state management Who this book is for This book is for JavaScript developers who have basic knowledge of React and who want to harness the power and flexibility of React Router
    Note: Description based on online resource; title from title page (Safari, viewed November 6, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789532555/?ar
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    Reinforcement learning with TensorFlow : a beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788830713 , 1788830717
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Reinforcement learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of the Reinforcement Learning techniques to develop self-learning systems using Tensorflow About This Book Learn reinforcement learning concepts and their implementation using TensorFlow Discover different problem-solving methods for Reinforcement Learning Apply reinforcement learning for autonomous driving cars, robobrokers, and more Who This Book Is For If you want to get started with reinforcement learning using TensorFlow in the most practical way, this book will be a useful resource. The book assumes prior knowledge of machine learning and neural network programming concepts, as well as some understanding of the TensorFlow framework. No previous experience with Reinforcement Learning is required. What You Will Learn Implement state-of-the-art Reinforcement Learning algorithms from the basics Discover various techniques of Reinforcement Learning such as MDP, Q Learning and more Learn the applications of Reinforcement Learning in advertisement, image processing, and NLP Teach a Reinforcement Learning model to play a game using TensorFlow and the OpenAI gym Understand how Reinforcement Learning Applications are used in robotics In Detail Reinforcement Learning (RL), allows you to develop smart, quick and self-learning systems in your business surroundings. It is an effective method to train your learning agents and solve a variety of problems in Artificial Intelligence - from games, self-driving cars and robots to enterprise applications that range from datacenter energy saving (cooling data centers) to smart warehousing solutions. The book covers the major advancements and successes achieved in deep reinforcement learning by synergizing deep neural network architectures with reinforcement learning. The book also introduces readers to the concept of Reinforcement Learning, its advantages and why it's gaining so much popularity. The book also discusses on MDPs, Monte Carlo tree searches, dynamic programming such as policy and value iteration, temporal difference learning such as Q-learning and SARSA. You will use TensorFlow and OpenAI Gym to build simple neural network models that learn from their own actions. You will also see how reinforcement learning algorithms play a role in games, image processing and NLP. By the end of this book, you will have a firm understanding of what reinforcement learning is and how to put your knowledge to practical use by leveraging the power of TensorFlow and OpenAI Gym. Style and approach A...
    Note: Description based on online resource; title from title page (Safari, viewed June 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788835725/?ar
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  • 82
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    Deep learning for computer vision : expert techniques to train advanced neural networks using TensorFlow and Keras (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788293358 , 1788293355
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks About This Book Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more Includes tips on optimizing and improving the performance of your models under various constraints Who This Book Is For This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python-and some understanding of machine learning concepts-is required to get the best out of this book. What You Will Learn Set up an environment for deep learning with Python, TensorFlow, and Keras Define and train a model for image and video classification Use features from a pre-trained Convolutional Neural Network model for image retrieval Understand and implement object detection using the real-world Pedestrian Detection scenario Learn about various problems in image captioning and how to overcome them by training images and text together Implement similarity matching and train a model for face recognition Understand the concept of generative models and use them for image generation Deploy your deep learning models and optimize them for high performance In Detail Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. Style and approach This book will teach advanced techniques for Computer Vision, applying the deep learning model in reference to various datasets. Downloading the example code for this...
    Note: Description based on online resource; title from title page (viewed February 21, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788295628/?ar
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  • 83
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    Angular 6 for enterprise-ready web applications : deliver production-ready and cloud-scale Angular web apps (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781786463760 , 1786463768
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: AngularJS (Software framework) ; Application software ; Development ; Web applications ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: A hands-on guide with a minimalist and flexible approach that enables quick learning and rapid delivery of cloud-ready enterprise applications with Angular 6 About This Book Explore tools and techniques to push your web app to the next level Master Angular app design and architectural considerations Learn continuous integration and deploy your app on a highly available cloud infrastructure in AWS Who This Book Is For This book is for developers who want to confidently deliver high-quality and production-grade Angular apps from design to deployment. We assume that you have prior experience in writing a RESTful API with the tech stack of your choice; if you don't, you can still gain a lot of benefit from this book, which focuses on the entire scope of frontend development, from design to deployment! What You Will Learn Create full-stack web applications using Angular and RESTful APIs Master Angular fundamentals, RxJS, CLI tools, unit testing, GitHub, and Docker Design and architect responsive, secure and scalable apps to deploy on AWS Adopt a minimalist, value-first approach to delivering your app with Kanban Get introduced to automated testing with continuous integration on CircleCI Optimize Nginx and Node.js web servers with load testing tools In Detail Angular 6 for Enterprise-Ready Web Applications follows a hands-on and minimalist approach demonstrating how to design and architect high quality apps. The first part of the book is about mastering the Angular platform using foundational technologies. You will use the Kanban method to focus on value delivery, communicate design ideas with mock-up tools and build great looking apps with Angular Material. You will become comfortable using CLI tools, understand reactive programming with RxJS, and deploy to the cloud using Docker. The second part of the book will introduce you to the router-first architecture, a seven-step approach to designing and developing mid-to-large line-of-business applications, along with popular recipes. You will learn how to design a solid authentication and authorization experience; explore unit testing, early integration with backend APIs using Swagger and continuous integration using CircleCI. In the concluding chapters, you will provision a highly available cloud infrastructure on AWS and then use Google Analytics to capture user behavior. By the end of this book, you will be familiar with the scope of web development using Angular, Swagger, and Docker, learning patte...
    Note: Description based on online resource; title from title page (Safari, viewed June 27, 2018)
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    Deep learning essentials : your hands-on guide to the fundamentals of deep learning and neural network modeling (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781785887772 , 1785887777
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Get to grips with the essentials of deep learning by leveraging the power of Python About This Book Your one-stop solution to get started with the essentials of deep learning and neural network modeling Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner Who This Book Is For Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python. What You Will Learn Get to grips with the core concepts of deep learning and neural networks Set up deep learning library such as TensorFlow Fine-tune your deep learning models for NLP and Computer Vision applications Unify different information sources, such as images, text, and speech through deep learning Optimize and fine-tune your deep learning models for better performance Train a deep reinforcement learning model that plays a game better than humans Learn how to make your models get the best out of your GPU or CPU In Detail Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while traini...
    Note: Description based on online resource; title from title page (Safari, viewed February 22, 2018)
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  • 85
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    Generative adversarial networks cookbook : over 100 recipes to build generative models using Python, TensorFlow, and Keras (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789139587 , 1789139589
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Machine learning ; Python (Computer program language) ; Artificial intelligence ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key Features Understand the common architecture of different types of GANs Train, optimize, and deploy GAN applications using TensorFlow and Keras Build generative models with real-world data sets, including 2D and 3D data Book Description Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand. This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use. By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away. What you will learn Structure a GAN architecture in pseudocode Understand the common architecture for each of the GAN models you will build Implement different GAN architectures in TensorFlow and Keras Use different datasets to enable neural network functionality in GAN models Combine different GAN models and learn how to fine-tune them Produce a model that can take 2D images and produce 3D models Develop a GAN to do style transfer with Pix2Pix Who this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.
    Note: Description based on online resource; title from title page (Safari, viewed February 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789139907/?ar
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    Modern JavaScript web development cookbook : easy solutions to common and everyday JavaScript development problems (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788992350 , 1788992350
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Web site development ; Web sites ; Design ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Over 90 recipes to help you write clean code, solve common JavaScript problems, and work on popular use cases like SPAs, microservices, native mobile development with Node, React, React Native and Electron. Key Features Over 90 practical recipes to help you write clean and maintainable JavaScript codes with the latest ES8 Leverage the power of leading web frameworks like Node and React to build modern web apps Features comprehensive coverage of tools and techniques needed to create multi-platform apps with JavaScript Book Description JavaScript has evolved into a language that you can use on any platform. Modern JavaScript Web Development Cookbook is a perfect blend of solutions for traditional JavaScript development and modern areas that developers have lately been exploring with JavaScript. This comprehensive guide teaches you how to work with JavaScript on servers, browsers, mobile phones and desktops. You will start by exploring the new features of ES8. You will then move on to learning the use of ES8 on servers (with Node.js), with the objective of producing services and microservices and dealing with authentication and CORS. Once you get accustomed to ES8, you will learn to apply it to browsers using frameworks, such as React and Redux, which interact through Ajax with services. You will then understand the use of a modern framework to develop the UI. In addition to this, development for mobile devices with React Native will walk you through the benefits of creating native apps, both for Android and iOS. Finally, you'll be able to apply your new-found knowledge of server-side and client-side tools to develop applications with Electron. What you will learn Use the latest features of ES8 and learn new ways to code with JavaScript Develop server-side services and microservices with Node.js Learn to do unit testing and to debug your code Build client-side web applications using React and Redux Create native mobile applications for Android and iOS with React Native Write desktop applications with Electron Who this book is for This book is for developers who want to explore the latest JavaScript features, frameworks, and tools for building complete mobile, desktop and web apps, including server and client-side code. You are expected to have working knowledge of JavaScript to get the most out of this book.
    Note: Description based on online resource; title from title page (Safari, viewed February 22, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781788992749/?ar
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    Building applications with Spring 5 and Vue.js 2 : build a modern, full-stack web application using Spring Boot and Vuex (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788831253 , 178883125X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spring (Software framework) ; Application software ; Development ; Cloud computing ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Become efficient in both frontend and backend web development with Spring and Vue Key Features Connect application's frontend and backend with Vue, Vuex, and Spring Boot Leverage the latest web standards to enhance code performance, readability, and cross-compatibility Build secure full-stack web applications with Spring Security Book Description Building Applications with Spring 5 and Vue.js 2, with its practical approach, helps you become a full-stack web developer. As well as knowing how to write frontend and backend code, a developer has to tackle all problems encountered in the application development life cycle ? starting from the simple idea of an application, to the UI and technical designs, and all the way to implementation, testing, production deployment, and monitoring. With the help of this book, you'll get to grips with Spring 5 and Vue.js 2 as you learn how to develop a web application. From the initial structuring to full deployment, you'll be guided at every step of developing a web application from scratch with Vue.js 2 and Spring 5. You'll learn how to create different components of your application as you progress through each chapter, followed by exploring different tools in these frameworks to expedite your development cycle. By the end of this book, you'll have gained a complete understanding of the key design patterns and best practices that underpin professional full-stack web development. What you will learn Analyze requirements and design data models Develop a single-page application using Vue.js 2 and Spring 5 Practice concept, logical, and physical data modeling Design, implement, secure, and test RESTful API Add test cases to improve reliability of an application Monitor and deploy your application to production Who this book is for Building Applications with Spring 5.0 and Vue.js 2.0 is for you if you are developer who is new to Vue.js or Spring. It is assumed that you have some knowledge of HTML, CSS, and Java.
    Note: Description based on online resource; title from title page (Safari, viewed December 3, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788836968/?ar
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    React 16 tooling : master essential cutting-edge tools, such as create-react-app, Jest, and Flow (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788832083 , 1788832086
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Application software ; Development ; Web site development ; Electronic books ; Electronic books ; local
    Abstract: React 16 Tooling covers the most important tools, utilities, and libraries that every React developer needs to know - in detail. About This Book Each chapter presents meta-development solutions to help React developers The tools used are presented in a practical, solution-oriented approach with no fluff The chapters are arranged in a logical order that mirrors a typical React development workflow, but you are free to tweak the approaches discussed to fit your own unique style Who This Book Is For This book is for React developers of any skill level who want to make their lives easier. It helps to have some familiarity with React, but if you are an experienced web developer looking at React, then this book will show you how to build a resilient toolset around you before you begin. What You Will Learn Bootstrap a React application using create-react-app Isolate React component development using Storybook Write effective unit tests for your React components using Jest Ensure that your component code is to standard using ESLint Use browser extensions and built-in component instrumentation to debug React applications Enable type safety in React components with Flowtype Deploy React applications inside a Docker container as part of a larger application stack In Detail React 16 Tooling covers the most important tools, utilities, and libraries that every React developer needs to know - in detail. As React has grown, the amazing toolset around it has also grown, adding features and enhancing the development workflow. Each of these essential tools is presented in a practical manner and in a logical order mirroring the development workflow. These tools will make your development life simpler and happier, enabling you to create better and more performant apps. Adam starts with a hand-picked selection of the best tools for the React 16 ecosystem. For starters, there's the create-react-app utility that's officially supported by the React team. Not only does this tool bootstrap your React project for you, it also provides a consistent and stable framework to build upon. The premise is that when you don't have to think about meta development work, more focus goes into the product itself. Other React tools follow this same approach to automating and improving your development life. Jest makes unit testing quicker. Flow makes catching errors easier. Docker containers make deployment in a stack simpler. Storybook makes developing components straightforward. ESLi...
    Note: Description based on online resource; title from title page (Safari, viewed May 31, 2018)
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    Node.js web development : server-side development with Node 10 made easy (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788627368 , 1788627369
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Fourth edition.
    Keywords: Node.js ; JavaScript (Computer program language) ; Web site development ; Electronic books ; Electronic books ; local
    Abstract: Create real-time applications using Node.js 10, Docker, MySQL, MongoDB, and Socket.IO with this practical guide and go beyond the developer's laptop to cover live deployment, including HTTPS and hardened security. About This Book Learn server-side JavaScript coding through the most up-to-date book on Node.js Explore the latest JavaScript features, and EcmaScript modules Walk through different stages of developing robust applications using Node.js 10 Who This Book Is For This book is for anybody looking for an alternative to the "P" languages (Perl, PHP, and Python), or anyone looking for a new paradigm of server-side application development. You should have at least a rudimentary understanding of JavaScript and web application development. What You Will Learn Install and use Node.js 10 for both development and deployment Use the Express 4.16 application framework Work with REST service development using the Restify framework Use data storage engines such as MySQL, SQLITE3, and MongoDB Use User authentication methods with OAuth2 Perform Real-time communication with the front-end using Socket.IO Implement Docker microservices in development, testing and deployment Perform unit testing with Mocha 5.x, and functional testing with Puppeteer 1.1.x Work with HTTPS using Let's Encrypt, and application security with Helmet In Detail Node.js is a server-side JavaScript platform using an event-driven, non-blocking I/O model allowing users to build fast and scalable data-intensive applications running in real time. This book gives you an excellent starting point, bringing you straight to the heart of developing web applications with Node.js. You will progress from a rudimentary knowledge of JavaScript and server-side development to being able to create, maintain, deploy and test your own Node.js application.You will understand the importance of transitioning to functions that return Promise objects, and the difference between fs, fs/promises and fs-extra. With this book you'll learn how to use the HTTP Server and Client objects, data storage with both SQL and MongoDB databases, real-time applications with Socket.IO, mobile-first theming with Bootstrap, microservice deployment with Docker, authenticating against third-party services using OAuth, and use some well known tools to beef up security of Express 4.16 applications. Style and approach Benefit from an easy, step-by-step approach that really works. Downloading the example code for this book You can d...
    Note: Description based on online resource; title from title page (Safari, viewed June 21, 2018)
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    Architecting Angular applications with Redux, RxJS, and NgRx : learn to build Redux style high-performing applications with Angular 6 (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787121751 , 1787121755
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: AngularJS (Software framework) ; Application software ; Development ; Web applications ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Manage state in Angular to write high performing web apps by combining the power of Flux, RxJS, and NgRx About This Book Learn what makes an excellent Angular application architecture Use Redux to write performant, consistent Angular applications Incorporate Reactive Programming principles and RxJS to make it easier to develop, test, and debug your Angular applications Who This Book Is For If you have been developing Angular applications and want to dive deeper into the Angular architecture with Redux, RxJS, and NgRx to write robust web apps, then this book is for you. What You Will Learn Understand the one-way data flow and Flux pattern Work with functional programming and asynchronous data streams Figure out how RxJS can help us address the flaws in promises Set up different versions of cascading calls Explore advanced operators Get familiar with the Redux pattern and its principles Test and debug different features of your application Build your own lightweight app using Flux, Redux, and NgRx In Detail Managing the state of large-scale web applications is a highly challenging task with the need to align different components, backends, and web workers harmoniously. When it comes to Angular, you can use NgRx, which combines the simplicity of Redux with the reactive programming power of RxJS to build your application architecture, making your code elegant and easy to reason about, debug, and test. In this book, we start by looking at the different ways of architecting Angular applications and some of the patterns that are involved in it. This will be followed by a discussion on one-way data flow, the Flux pattern, and the origin of Redux. The book introduces you to declarative programming or, more precisely, functional programming and talks about its advantages. We then move on to the reactive programming paradigm. Reactive programming is a concept heavily used in Angular and is at the core of NgRx. Later, we look at RxJS, as a library and master it. We thoroughly describe how Redux works and how to implement it from scratch. The two last chapters of the book cover everything NgRx has to offer in terms of core functionality and supporting libraries, including how to build a micro implementation of NgRx. This book will empower you to not only use Redux and NgRx to the fullest, but also feel confident in building your own version, should you need it. Style and approach This book covers everything there is to know to get well-acquainted with Ang...
    Note: Description based on online resource; title from title page (Safari, viewed May 2, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781787122406/?ar
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    Ethereum cookbook : over 100 recipes covering Ethereum-based tokens, games, wallets, smart contracts, protocols, and Dapps (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789137941 , 1789137942
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Electronic data processing ; Distributed processing ; Blockchains (Databases) ; Distributed databases ; JavaScript (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Mine Ether, deploy smart contracts, tokens, and ICOs, and manage security vulnerabilities of Ethereum Key Features Build end-to-end decentralized Ethereum apps using Truffle, Web3, and Solidity Explore various solution-based recipes to build smart contracts and foolproof decentralized applications Develop decentralized marketplaces from scratch, build wallets, and manage transactions Book Description Ethereum and Blockchain will change the way software is built for business transactions. Most industries have been looking to leverage these new technologies to gain efficiencies and create new business models and opportunities. The Ethereum Cookbook covers various solutions such as setting up Ethereum, writing smart contracts, and creating tokens, among others. You'll learn about the security vulnerabilities, along with other protocols of Ethereum. Once you have understood the basics, you'll move on to exploring various design decisions and tips to make your application scalable and secure. In addition to this, you'll work with various Ethereum packages such as Truffle, Web3, and Ganache. By the end of this book, you'll have comprehensively grasped the Ethereum principles and ecosystem. What you will learn Efficiently write smart contracts in Ethereum Build scalable distributed applications and deploy them Use tools and frameworks to develop, deploy, and test your application Use block explorers such as Etherscan to find a specific transaction Create your own tokens, initial coin offerings (ICOs), and games Understand various security flaws in smart contracts in order to avoid them Who this book is for The Ethereum Cookbook is for you if you are a software engineer, Blockchain developer, or research scientist who wants to build smart contracts, develop decentralized applications, and facilitate peer-to-peer transaction. It is assumed that you are familiar with Blockchain concepts and have sound knowledge of JavaScript.
    Note: Description based on online resource; title from title page (Safari, viewed October 1, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789133998/?ar
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  • 92
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    Next.js quick start guide : server-side rendering done right (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788995849 , 1788995848
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: JavaScript (Computer program language) ; Application software ; Development ; Web applications ; Electronic books ; Electronic books ; local
    Abstract: Create, build and deploy universal JavaScript applications using Next.js Key Features Work with the entire tool-chain for developing universal Javascript applications with Next.js A straightforward guide to implementing server-side rendering Use Next.js to build SEO-friendly and super fast websites Book Description Next.js is a powerful addition to the ever-growing and dynamic JavaScript world. Built on top of React, Webpack, and Babel, it is a minimalistic framework for server-rendered universal JavaScript applications. This book will show you the best practices for building sites using Next. js, enabling you to build SEO-friendly and superfast websites. This book will guide you from building a simple single page app to a scalable and reliable client-server infrastructure. You will explore code sharing between client and server, universal modules, and server-side rendering. The book will take you through the core Next.js concepts that everyone is talking about ? hot reloading, code splitting, routing, server rendering, transpilation, CSS isolation, and more. You will learn ways of implementing them in order to create your own universal JavaScript application. You will walk through the building and deployment stages of your applications with the JSON API,customizing the confguration, error handling,data fetching, deploying to production, and authentication. What you will learn Explore the benefts of server-side rendering with Next.js Create and link JavaScript modules together by understanding code splitting and bundling Create website pages and wire them together through website navigation Extend your application with additional Webpack loaders and features, as well as custom Babel plugins and presets Use GraphQL and Apollo frameworks with Next.js to fetch data and receive push notifcations Design and implement core modules, such as logging and authentication, and then more complex solutions for access control and business rule management Write tests and use online CI tools such as Travis, GitLab, and more Build a Docker-based container for your app and deploy it to online services such as Heroku and Now.sh Who this book is for This book is for JavaScript developers who want to learn how to generate server-rendered applications.
    Note: Description based on online resource; title from title page (Safari, viewed August 27, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788993661/?ar
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  • 93
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    R deep learning essentials : a step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788997805 , 1788997808
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: R (Computer program language) ; Artificial intelligence ; Machine learning ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for computer vision and text Apply deep learning techniques in cloud for large-scale processing Build, train, and optimize neural network models on a range of datasets Book Description Deep learning is a powerful subset of machine learning that is very successful in domains such as computer vision and natural language processing (NLP). This second edition of R Deep Learning Essentials will open the gates for you to enter the world of neural networks by building powerful deep learning models using the R ecosystem. This book will introduce you to the basic principles of deep learning and teach you to build a neural network model from scratch. As you make your way through the book, you will explore deep learning libraries, such as Keras, MXNet, and TensorFlow, and create interesting deep learning models for a variety of tasks and problems, including structured data, computer vision, text data, anomaly detection, and recommendation systems. You'll cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud. In the concluding chapters, you will learn about the theoretical concepts of deep learning projects, such as model optimization, overfitting, and data augmentation, together with other advanced topics. By the end of this book, you will be fully prepared and able to implement deep learning concepts in your research work or projects. What you will learn Build shallow neural network prediction models Prevent models from overfitting the data to improve generalizability Explore techniques for finding the best hyperparameters for deep learning models Create NLP models using Keras and TensorFlow in R Use deep learning for computer vision tasks Implement deep learning tasks, such as NLP, recommendation systems, and autoencoders Who this book is for This second edition of R Deep Learning Essentials is for aspiring data scientists, data analysts, machine learning developers, and deep learning enthusiasts who are well versed in machine learning concepts and are looking to explore the deep learning paradigm using R. Fundamental understanding of the R language is necessary to get the most out of this book.
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed October 8, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781788992893/?ar
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  • 94
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    Hands-on machine learning with Azure : build powerful models with cognitive machine learning and artificial intelligence (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789130270 , 1789130271
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Windows Azure ; Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Implement machine learning, cognitive services, and artificial intelligence solutions by leveraging Azure cloud technologies Key Features Learn advanced concepts in Azure ML and the Cortana Intelligence Suite architecture Explore ML Server using SQL Server and HDInsight capabilities Implement various tools in Azure to build and deploy machine learning models Book Description Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way. The book begins by covering the benefits of ML and AI in the cloud. You will then explore Microsoft's Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications. This book lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The book then takes you through a preconfigured series of virtual machines in Azure targeted at AI development scenarios. You will get to grips with the ML Server and its capabilities in SQL and HDInsight. In the concluding chapters, you'll integrate patterns with other non-AI services in Azure. By the end of this book, you will be fully equipped to implement smart cognitive actions in your models. What you will learn Discover the benefits of leveraging the cloud for ML and AI Use Cognitive Services APIs to build intelligent bots Build a model using canned algorithms from Microsoft and deploy it as a web service Deploy virtual machines in AI development scenarios Apply R, Python, SQL Server, and Spark in Azure Build and deploy deep learning solutions with CNTK, MMLSpark, and TensorFlow Implement model retraining in IoT, Streaming, and Blockchain solutions Explore best practices for integrating ML and AI functions with ADLA and logic apps Who this book is for If you are a data scientist or developer familiar with Azure ML and cognitive services and want to create smart models and make sense of data in the cloud, this book is for you. You'll also find this book useful if you want to bring powerful mach...
    Note: Includes bibliographical references. . - Description based on online resource; title from title page (Safari, viewed March 20, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781789131956/?ar
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  • 95
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    Hands-on convolutional neural networks with TensorFlow : solve computer vision problems with modeling in TensorFlow and Python (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789132823 , 1789132827
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Machine learning ; Artificial intelligence ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for image classification, image recognition, object detection and many computer vision challenges. Key Features Learn the fundamentals of Convolutional Neural Networks Harness Python and Tensorflow to train CNNs Build scalable deep learning models that can process millions of items Book Description Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time! We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation. After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks. Later on, you will see useful tips on machine learning best practices and troubleshooting. Finally, you will learn how to apply your models on large datasets of millions of images. What you will learn Train machine learning models with TensorFlow Create systems that can evolve and scale during their life cycle Use CNNs in image recognition and classification Use TensorFlow for building deep learning models Train popular deep learning models Fine-tune a neural network to improve the quality of results with transfer learning Build TensorFlow models that can scale to large datasets and systems Who this book is for This book is for Software Engineers, Data Scientists, or Machine Learning practitioners who want to use CNNs for solving real-world problems. Knowledge of basic machine learning concepts, linear algebra and Python will help.
    Note: Description based on online resource; title from title page (Safari, viewed October 5, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781789130331/?ar
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  • 96
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    Python deep learning projects : 9 projects demystifying neural network and deep learning models for building intelligent systems (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789134759 , 1789134757
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Insightful practical projects to master deep learning and neural network architectures using Python, Keras and MXNet About This Book Rich projects on computer vision, NLP, and image processing Build your own neural network and explore innumerable possibilities with deep learning Explore the power of Python for deep learning in various scenarios using insightful projects Who This Book Is For This book is for developers, data scientists, or enthusiasts, who have sound knowledge of python programming, basics of machine learning, and want to break into deep learning, either for opening a new career opportunity or for realizing their own AI projects. What You Will Learn Set up a Deep Learning development environment on AWS, using GPU-powered instances and the Deep Learning AMI Implement Sequence to Sequence Networks for modeling natural language processing Develop an end-to-end speech recognition system Build a system for pixel-wise semantic labeling of an image Develop a system that generates images and their regions In Detail Deep Learning has quietly revolutionized every field of Artificial Intelligence, enabling the development of applications that a few years ago were considered almost impossible. This book will provide all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each new project will build upon the experience and knowledge accumulated in the previous ones, allowing the reader to progressively master the subject. You will learn neural network models implementing a text classifier system using Recurrent Neural network model (RNN) and optimize it to understand the shortcomings you might come across while implementing a simple deep learning system. If you are looking to implement intelligent systems like Automatic Machine Translation, Handwriting Generation, Character Text Generation, Object Classification in Photographs, Colorization of Images, Image Caption Generation, Character Text Generation or Automatic Game Playing into your application then this book is for you. By the end of this book, you will come across various Recurrent and Convolutional Neural network implementations with practical hands-on to modeling concepts like regularization, Gradient clipping, and gradient normalization, LSTM, Bidirectional RNN's through a series engaging projects. Style and approach One stop guide to gain deep learning knowledge and skills by working on authentic, engagin...
    Note: Description based on online resource; title from title page (Safari, viewed March 1, 2019)
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    Machine learning with Swift : artificial intelligence for iOS (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781787123526 , 1787123529
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: iOS (Electronic resource) ; Swift (Computer program language) ; Machine learning ; Artificial intelligence ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease About This Book Implement effective machine learning solutions for your iOS applications Use Swift and Core ML to build and deploy popular machine learning models Develop neural networks for natural language processing and computer vision Who This Book Is For iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book. What You Will Learn Learn rapid model prototyping with Python and Swift Deploy pre-trained models to iOS using Core ML Find hidden patterns in the data using unsupervised learning Get a deeper understanding of the clustering techniques Learn modern compact architectures of neural networks for iOS devices Train neural networks for image processing and natural language processing In Detail Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We'll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves. Style and approach A comprehensive guide that teaches how to implement machine learning apps for iOS from scratc 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 regi...
    Note: Description based on online resource; title from title page (Safari, viewed March 20, 2018)
    URL: https://learning.oreilly.com/library/view/-/9781787121515/?ar
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  • 98
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    Mastering ServiceNow scripting : leverage JavaScript APIs to perform client-side and server-side scripting on ServiceNow instances (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788624206 , 1788624203
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Information technology Management ; Application software Development ; JavaScript (Computer program language) ; Application program interfaces (Computer software) ; Enterprise resource planning
    Note: Description based on online resource; title from title page (Safari, viewed March 21, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: lizenzpflichtig
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  • 99
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    Vue.js quick start guide : lean how to build amazing and complex reactive web applications easily using Vue.js (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781789344172 , 1789344174 , 9781789344103
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Application software Development ; Web applications ; JavaScript (Computer program language) ; Application software ; Development ; JavaScript (Computer program language) ; Web applications ; Electronic books
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed January 10, 2019)
    URL: lizenzpflichtig
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  • 100
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    Hands-on Markov models with Python : implement probabilistic models for learning complex data sequences using Python ecosystem (2018)
    Birmingham, UK : Packt Publishing
    Details
    ISBN: 9781788629331 , 1788629337 , 9781788625449
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    DDC: 005.133
    Keywords: Markov processes Numerical solutions ; Python (Computer program language) ; Machine learning ; Natural language processing (Computer science) ; Artificial intelligence ; Neural networks & fuzzy systems ; Natural language & machine translation ; Computers ; Intelligence (AI) & Semantics ; Computers ; Neural Networks ; Computers ; Natural Language Processing ; Machine learning ; Markov processes ; Numerical solutions ; Natural language processing (Computer science) ; Python (Computer program language) ; Electronic books
    Note: Online resource; title from title page (Safari, viewed November 2, 2018)
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