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Automating Workflows with GitHub Actions

Author : Priscila Heller
Publisher : Packt Publishing Ltd
ISBN 13 : 1800569033
Total Pages : 216 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Automating Workflows with GitHub Actions by : Priscila Heller

Download or read book Automating Workflows with GitHub Actions written by Priscila Heller and published by Packt Publishing Ltd. This book was released on 2021-11-11 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build, test, and deploy code right from your GitHub repository by automating, customizing, and executing software development workflows with GitHub Actions Key FeaturesEnhance your CI/CD and DevOps workflows using GitHub ActionsDiscover how to create custom GitHub Actions using Docker and JavaScriptGet up and running with building a CI/CD pipeline effectivelyBook Description GitHub Actions is one of the most popular products that enables you to automate development tasks and improve your software development workflow. Automating Workflows with GitHub Actions uses real-world examples to help you automate everyday tasks and use your resources efficiently. This book takes a practical approach to helping you develop the skills needed to create complex YAML files to automate your daily tasks. You'll learn how to find and use existing workflows, allowing you to get started with GitHub Actions right away. Moving on, you'll discover complex concepts and practices such as self-hosted runners and writing workflow files that leverage other platforms such as Docker as well as programming languages such as Java and JavaScript. As you advance, you'll be able to write your own JavaScript, Docker, and composite run steps actions, and publish them in GitHub Marketplace! You'll also find instructions to migrate your existing CI/CD workflows into GitHub Actions from platforms like Travis CI and GitLab. Finally, you'll explore tools that'll help you stay informed of additions to GitHub Actions along with finding technical support and staying engaged with the community. By the end of this GitHub book, you'll have developed the skills and experience needed to build and maintain your own CI/CD pipeline using GitHub Actions. What you will learnGet to grips with the basics of GitHub and the YAML syntaxUnderstand key concepts of GitHub ActionsFind out how to write actions for JavaScript and Docker environmentsDiscover how to create a self-hosted runnerMigrate from other continuous integration and continuous delivery (CI/CD) platforms to GitHub ActionsCollaborate with the GitHub Actions community and find technical help to navigate technical difficultiesPublish your workflows in GitHub MarketplaceWho this book is for This book is for anyone involved in the software development life cycle, for those looking to learn about GitHub Actions and what can be accomplished, and for those who want to develop a new skill to help them advance their software development career. If you are new to GitHub and GitHub Actions in general, then this book is for you. Basic knowledge of GitHub as a platform will help you to get the most out of this book.

Learning GitHub Actions

Author : Brent Laster
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098131045
Total Pages : 414 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Learning GitHub Actions by : Brent Laster

Download or read book Learning GitHub Actions written by Brent Laster and published by "O'Reilly Media, Inc.". This book was released on 2023-08-17 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automate your software development processes with GitHub Actions, the continuous integration and continuous delivery platform that integrates seamlessly with GitHub. With this practical book, open source author, trainer, and DevOps director Brent Laster explains everything you need to know about using and getting value from GitHub Actions. You'll learn what actions and workflows are and how they can be used, created, and incorporated into your processes to simplify, standardize, and automate your work in GitHub. This book explains the platform, components, use cases, implementation, and integration points of actions, so you can leverage them to provide the functionality and features needed in today's complex pipelines and software development processes. You'll learn how to design and implement automated workflows that respond to common events like pushes, pull requests, and review updates. You'll understand how to use the components of the GitHub Actions platform to gain maximum automation and benefit. With this book, you will: Learn what GitHub Actions are, the various use cases for them, and how to incorporate them into your processes Understand GitHub Actions' structure, syntax, and semantics Automate processes and implement functionality Create your own custom actions with Docker, JavaScript, or shell approachesTroubleshoot and debug workflows that use actions Combine actions with GitHub APIs and other integration options Identify ways to securely implement workflows with GitHub Actions Understand how GitHub Actions compares to other options

Hands-on GitHub Actions

Author : Chaminda Chandrasekara
Publisher : Apress
ISBN 13 : 9781484264638
Total Pages : 162 pages
Book Rating : 4.2/5 (646 download)

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Book Synopsis Hands-on GitHub Actions by : Chaminda Chandrasekara

Download or read book Hands-on GitHub Actions written by Chaminda Chandrasekara and published by Apress. This book was released on 2021-02-23 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implement continuous integration/continuous delivery (CI/CD) workflows for any application you develop through GitHub Actions. This book will give you an in-depth idea of implementation patterns, solutions for different technology builds, guidelines to implement your own custom components as actions, and usage of features available with GitHub Actions workflows, to set up CI/CD for your repositories. Hands-on GitHub Actions starts with an introduction to GitHub actions that gives an overview on CI/CD followed by an introduction to its workflows. Next, you will learn how to use variables in a GitHub workflow along with tokens via a REST API. Further, you will explore artifacts and caching dependencies in GitHub and use artifacts in subsequent jobs. Using self-hosted runners is discussed next where you will set up your own hardware and software to run GitHub actions. You will go through publishing packages and migrate to Azure DevOps Pipelines. Along the way, you will use Redis service and PostgreSQL service containers and create custom actions. Finally, you will work with GitHub apps and understand the syntax reference for GitHub Actions and workflows. What You Will Learn Create workflows for any platform and any language with GitHub Actions Develop custom GitHub actions to enhance features and usage of database and service containers Use hosted runners and create self-hosted runners for GitHub workflows Use GitHub Package registry with GitHub Actions to share and use packages Who This Book Is For DevOps teams who want to build quality CI/CD workflows.

Learning GitHub Actions

Author : Brent Laster
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098131037
Total Pages : 424 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Learning GitHub Actions by : Brent Laster

Download or read book Learning GitHub Actions written by Brent Laster and published by "O'Reilly Media, Inc.". This book was released on 2023-08-17 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automate your software development processes with GitHub Actions, the continuous integration and continuous delivery platform that integrates seamlessly with GitHub. With this practical book, open source author, trainer, and DevOps director Brent Laster explains everything you need to know about using and getting value from GitHub Actions. You'll learn what actions and workflows are and how they can be used, created, and incorporated into your processes to simplify, standardize, and automate your work in GitHub. This book explains the platform, components, use cases, implementation, and integration points of actions, so you can leverage them to provide the functionality and features needed in today's complex pipelines and software development processes. You'll learn how to design and implement automated workflows that respond to common events like pushes, pull requests, and review updates. You'll understand how to use the components of the GitHub Actions platform to gain maximum automation and benefit. With this book, you will: Learn what GitHub Actions are, the various use cases for them, and how to incorporate them into your processes Understand GitHub Actions' structure, syntax, and semantics Automate processes and implement functionality Create your own custom actions with Docker, JavaScript, or shell approachesTroubleshoot and debug workflows that use actions Combine actions with GitHub APIs and other integration options Identify ways to securely implement workflows with GitHub Actions Understand how GitHub Actions compares to other options

Machine Learning in Action

Author : Peter Harrington
Publisher : Simon and Schuster
ISBN 13 : 1638352453
Total Pages : 558 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Machine Learning in Action by : Peter Harrington

Download or read book Machine Learning in Action written by Peter Harrington and published by Simon and Schuster. This book was released on 2012-04-03 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. About the Book A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many. Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification. Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside A no-nonsense introduction Examples showing common ML tasks Everyday data analysis Implementing classic algorithms like Apriori and Adaboos Table of Contents PART 1 CLASSIFICATION Machine learning basics Classifying with k-Nearest Neighbors Splitting datasets one feature at a time: decision trees Classifying with probability theory: naïve Bayes Logistic regression Support vector machines Improving classification with the AdaBoost meta algorithm PART 2 FORECASTING NUMERIC VALUES WITH REGRESSION Predicting numeric values: regression Tree-based regression PART 3 UNSUPERVISED LEARNING Grouping unlabeled items using k-means clustering Association analysis with the Apriori algorithm Efficiently finding frequent itemsets with FP-growth PART 4 ADDITIONAL TOOLS Using principal component analysis to simplify data Simplifying data with the singular value decomposition Big data and MapReduce

Learning GitHub Actions

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (12 download)

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Book Synopsis Learning GitHub Actions by :

Download or read book Learning GitHub Actions written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use GitHub Actions to automate many common developer tasks. Discover how to build workflows triggered by events, as well as how to create your own custom actions.

Deep Reinforcement Learning in Action

Author : Alexander Zai
Publisher : Manning Publications
ISBN 13 : 1617295434
Total Pages : 381 pages
Book Rating : 4.6/5 (172 download)

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Book Synopsis Deep Reinforcement Learning in Action by : Alexander Zai

Download or read book Deep Reinforcement Learning in Action written by Alexander Zai and published by Manning Publications. This book was released on 2020-04-28 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement Learning in Action teaches you the fundamental concepts and terminology of deep reinforcement learning, along with the practical skills and techniques you’ll need to implement it into your own projects. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Deep reinforcement learning AI systems rapidly adapt to new environments, a vast improvement over standard neural networks. A DRL agent learns like people do, taking in raw data such as sensor input and refining its responses and predictions through trial and error. About the book Deep Reinforcement Learning in Action teaches you how to program AI agents that adapt and improve based on direct feedback from their environment. In this example-rich tutorial, you’ll master foundational and advanced DRL techniques by taking on interesting challenges like navigating a maze and playing video games. Along the way, you’ll work with core algorithms, including deep Q-networks and policy gradients, along with industry-standard tools like PyTorch and OpenAI Gym. What's inside Building and training DRL networks The most popular DRL algorithms for learning and problem solving Evolutionary algorithms for curiosity and multi-agent learning All examples available as Jupyter Notebooks About the reader For readers with intermediate skills in Python and deep learning. About the author Alexander Zai is a machine learning engineer at Amazon AI. Brandon Brown is a machine learning and data analysis blogger. Table of Contents PART 1 - FOUNDATIONS 1. What is reinforcement learning? 2. Modeling reinforcement learning problems: Markov decision processes 3. Predicting the best states and actions: Deep Q-networks 4. Learning to pick the best policy: Policy gradient methods 5. Tackling more complex problems with actor-critic methods PART 2 - ABOVE AND BEYOND 6. Alternative optimization methods: Evolutionary algorithms 7. Distributional DQN: Getting the full story 8.Curiosity-driven exploration 9. Multi-agent reinforcement learning 10. Interpretable reinforcement learning: Attention and relational models 11. In conclusion: A review and roadmap

Learning Processing

Author : Daniel Shiffman
Publisher : Newnes
ISBN 13 : 0123947928
Total Pages : 566 pages
Book Rating : 4.1/5 (239 download)

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Book Synopsis Learning Processing by : Daniel Shiffman

Download or read book Learning Processing written by Daniel Shiffman and published by Newnes. This book was released on 2015-09-09 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning Processing, Second Edition, is a friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages. Requiring no previous experience, this book is for the true programming beginner. It teaches the basic building blocks of programming needed to create cutting-edge graphics applications including interactive art, live video processing, and data visualization. Step-by-step examples, thorough explanations, hands-on exercises, and sample code, supports your learning curve. A unique lab-style manual, the book gives graphic and web designers, artists, and illustrators of all stripes a jumpstart on working with the Processing programming environment by providing instruction on the basic principles of the language, followed by careful explanations of select advanced techniques. The book has been developed with a supportive learning experience at its core. From algorithms and data mining to rendering and debugging, it teaches object-oriented programming from the ground up within the fascinating context of interactive visual media. This book is ideal for graphic designers and visual artists without programming background who want to learn programming. It will also appeal to students taking college and graduate courses in interactive media or visual computing, and for self-study. A friendly start-up guide to Processing, a free, open-source alternative to expensive software and daunting programming languages No previous experience required—this book is for the true programming beginner! Step-by-step examples, thorough explanations, hands-on exercises, and sample code supports your learning curve

Interpretable Machine Learning

Author : Christoph Molnar
Publisher : Lulu.com
ISBN 13 : 0244768528
Total Pages : 320 pages
Book Rating : 4.2/5 (447 download)

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Book Synopsis Interpretable Machine Learning by : Christoph Molnar

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Deep Learning and the Game of Go

Author : Kevin Ferguson
Publisher : Simon and Schuster
ISBN 13 : 1638354014
Total Pages : 611 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning and the Game of Go by : Kevin Ferguson

Download or read book Deep Learning and the Game of Go written by Kevin Ferguson and published by Simon and Schuster. This book was released on 2019-01-06 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios! What's inside Build and teach a self-improving game AI Enhance classical game AI systems with deep learning Implement neural networks for deep learning About the Reader All you need are basic Python skills and high school-level math. No deep learning experience required. About the Author Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo. Table of Contents PART 1 - FOUNDATIONS Toward deep learning: a machine-learning introduction Go as a machine-learning problem Implementing your first Go bot PART 2 - MACHINE LEARNING AND GAME AI Playing games with tree search Getting started with neural networks Designing a neural network for Go data Learning from data: a deep-learning bot Deploying bots in the wild Learning by practice: reinforcement learning Reinforcement learning with policy gradients Reinforcement learning with value methods Reinforcement learning with actor-critic methods PART 3 - GREATER THAN THE SUM OF ITS PARTS AlphaGo: Bringing it all together AlphaGo Zero: Integrating tree search with reinforcement learning

Learning GitHub Actions

Author : Michael Jenkins
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Learning GitHub Actions by : Michael Jenkins

Download or read book Learning GitHub Actions written by Michael Jenkins and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Docker in Practice, Second Edition

Author : Ian Miell
Publisher : Simon and Schuster
ISBN 13 : 1638356300
Total Pages : 707 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Docker in Practice, Second Edition by : Ian Miell

Download or read book Docker in Practice, Second Edition written by Ian Miell and published by Simon and Schuster. This book was released on 2019-02-06 with total page 707 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Docker in Practice, Second Edition presents over 100 practical techniques, hand-picked to help you get the most out of Docker. Following a Problem/Solution/Discussion format, you'll walk through specific examples that you can use immediately, and you'll get expert guidance on techniques that you can apply to a whole range of scenarios. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Docker's simple idea-wrapping an application and its dependencies into a single deployable container-created a buzz in the software industry. Now, containers are essential to enterprise infrastructure, and Docker is the undisputed industry standard. So what do you do after you've mastered the basics? To really streamline your applications and transform your dev process, you need relevant examples and experts who can walk you through them. You need this book. About the Book Docker in Practice, Second Edition teaches you rock-solid, tested Docker techniques, such as replacing VMs, enabling microservices architecture, efficient network modeling, offline productivity, and establishing a container-driven continuous delivery process. Following a cookbook-style problem/solution format, you'll explore real-world use cases and learn how to apply the lessons to your own dev projects. What's inside Continuous integration and delivery The Kubernetes orchestration tool Streamlining your cloud workflow Docker in swarm mode Emerging best practices and techniques About the Reader Written for developers and engineers using Docker in production. About the Author Ian Miell and Aidan Hobson Sayers are seasoned infrastructure architects working in the UK. Together, they used Docker to transform DevOps at one of the UK's largest gaming companies. Table of Contents PART 1 - DOCKER FUNDAMENTALS Discovering Docker Understanding Docker: Inside the engine room PART 2 - DOCKER AND DEVELOPMENT Using Docker as a lightweight virtual machine Building images Running containers Day-to-day Docker Configuration management: Getting your house in order PART 3 - DOCKER AND DEVOPS Continuous integration: Speeding up your development pipeline Continuous delivery: A perfect fit for Docker principles Network simulation: Realistic environment testing without the pain PART 4 - ORCHESTRATION FROM A SINGLE MACHINE TO THE CLOUD A primer on container orchestration The data center as an OS with Docker Docker platforms PART 5 - DOCKER IN PRODUCTION Docker and security Plain sailing: Running Docker in production Docker in production: Dealing with challenges

GitHub For Dummies

Author : Sarah Guthals
Publisher : John Wiley & Sons
ISBN 13 : 1119572673
Total Pages : 370 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis GitHub For Dummies by : Sarah Guthals

Download or read book GitHub For Dummies written by Sarah Guthals and published by John Wiley & Sons. This book was released on 2019-05-29 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Code collaboratively with GitHub Once you’ve learned the basics of coding the next step is to start sharing your expertise, learning from other coding pros, or working as a collaborative member of development teams. GitHub is the go-to community for facilitating coding collaboration, and GitHub For Dummies is the next step on your journey as a developer. Written by a GitHub engineer, this book is packed with insight on how GitHub works and how you can use it to become a more effective, efficient, and valuable member of any collaborative programming team. Store and share your work online with GitHub Collaborate with others on your team or across the international coding community Embrace open-source values and processes Establish yourself as a valuable member of the GitHub community From setting up GitHub on your desktop and launching your first project to cloning repositories, finding useful apps on the marketplace, and improving workflow, GitHub For Dummies covers the essentials the novice programmer needs to enhance collaboration and teamwork with this industry-standard tool.

Learn Git in a Month of Lunches

Author : Rick Umali
Publisher : Simon and Schuster
ISBN 13 : 1638353492
Total Pages : 596 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Learn Git in a Month of Lunches by : Rick Umali

Download or read book Learn Git in a Month of Lunches written by Rick Umali and published by Simon and Schuster. This book was released on 2015-09-01 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Learn Git in a Month of Lunches introduces the discipline of source code control using Git. Whether you're a newbie or a busy pro moving your source control to Git, you'll appreciate how this book concentrates on the components of Git you'll use every day. In easy-to-follow lessons designed to take an hour or less, you'll dig into Git's distributed collaboration model, along with core concepts like committing, branching, and merging. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book Git is the source code control system preferred by modern development teams. Its decentralized architecture and lightning-fast branching let you concentrate on your code instead of tedious version control tasks. At first, Git may seem like a sprawling beast. Fortunately, to get started you just need to master a few essential techniques. Read on! Learn Git in a Month of Lunches introduces the discipline of source code control using Git. Helpful for both newbies who have never used source control and busy pros, this book concentrates on the components of Git you'll use every day. In easy-to-follow lessons that take an hour or less, you'll dig into Git's distributed collaboration model, along with core concepts like committing, branching, and merging. This book is a road map to the commands and processes you need to be instantly productive. What's Inside Start from square one—no experience required The most frequently used Git commands Mental models that show how Git works Learn when and how to branch code About the Reader No previous experience with Git or other source control systems is required. About the Author Rick Umali uses Git daily as a developer and is a skilled consultant, trainer, and speaker. Table of Contents Before you begin An overview of Git and version control Getting oriented with Git Making and using a Git repository Using Git with a GUI Tracking and updating files in Git Committing parts of changes The time machine that is Git Taking a fork in the road Merging branches Cloning Collaborating with remotes Pushing your changes Keeping in sync Software archaeology Understanding git rebase Workflows and branching conventions Working with GitHub Third-party tools and Git Sharpening your Git

Reinforcement Learning, second edition

Author : Richard S. Sutton
Publisher : MIT Press
ISBN 13 : 0262352702
Total Pages : 549 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Reinforcement Learning, second edition by : Richard S. Sutton

Download or read book Reinforcement Learning, second edition written by Richard S. Sutton and published by MIT Press. This book was released on 2018-11-13 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.

GANs in Action

Author : Vladimir Bok
Publisher : Simon and Schuster
ISBN 13 : 1638354235
Total Pages : 367 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis GANs in Action by : Vladimir Bok

Download or read book GANs in Action written by Vladimir Bok and published by Simon and Schuster. This book was released on 2019-09-09 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning systems have gotten really great at identifying patterns in text, images, and video. But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks' one that generates content and the other that rejects samples that are of poor quality. GANs in Action: Deep learning with Generative Adversarial Networks teaches you how to build and train your own generative adversarial networks. First, you'll get an introduction to generative modelling and how GANs work, along with an overview of their potential uses. Then, you'll start building your own simple adversarial system, as you explore the foundation of GAN architecture: the generator and discriminator networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

Pragmatic AI

Author : Noah Gift
Publisher : Addison-Wesley Professional
ISBN 13 : 0134863917
Total Pages : 720 pages
Book Rating : 4.1/5 (348 download)

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Book Synopsis Pragmatic AI by : Noah Gift

Download or read book Pragmatic AI written by Noah Gift and published by Addison-Wesley Professional. This book was released on 2018-07-12 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.