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Introducing Github
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Download or read book Introducing GitHub written by Peter Bell and published by "O'Reilly Media, Inc.". This book was released on 2014-11-11 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you’re new to GitHub, this concise book shows you just what you need to get started and no more. It’s perfect for project and product managers, stakeholders, and other team members who want to collaborate on a development project—whether it’s to review and comment on work in progress or to contribute specific changes. It’s also great for developers just learning GitHub. GitHub has rapidly become the default platform for software development, but it’s also ideal for other text-based documents, from contracts to screenplays. This hands-on book shows you how to use GitHub’s web interface to view projects and collaborate effectively with your team. Learn how and why people use GitHub to collaborate View the status of a project—recent changes, outstanding work, and historic changes Create and edit files through GitHub without learning Git Suggest changes to projects you don’t have permission to edit directly Use tools like issues, pull requests, and branches to specify and collaborate on changes Create a new GitHub repository to control who has access to your project
Book Synopsis Introduction to Machine Learning with Python by : Andreas C. Müller
Download or read book Introduction to Machine Learning with Python written by Andreas C. Müller and published by "O'Reilly Media, Inc.". This book was released on 2016-09-26 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you’ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills
Book Synopsis Introduction to Data Science by : Laura Igual
Download or read book Introduction to Data Science written by Laura Igual and published by Springer. This book was released on 2017-02-22 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
Download or read book Introducing GitHub written by Peter Bell and published by "O'Reilly Media, Inc.". This book was released on 2014-11-11 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you’re new to GitHub, this concise book shows you just what you need to get started and no more. It’s perfect for project and product managers, stakeholders, and other team members who want to collaborate on a development project—whether it’s to review and comment on work in progress or to contribute specific changes. It’s also great for developers just learning GitHub. GitHub has rapidly become the default platform for software development, but it’s also ideal for other text-based documents, from contracts to screenplays. This hands-on book shows you how to use GitHub’s web interface to view projects and collaborate effectively with your team. Learn how and why people use GitHub to collaborate View the status of a project—recent changes, outstanding work, and historic changes Create and edit files through GitHub without learning Git Suggest changes to projects you don’t have permission to edit directly Use tools like issues, pull requests, and branches to specify and collaborate on changes Create a new GitHub repository to control who has access to your project
Download or read book Introducing GitHub written by Brent Beer and published by "O'Reilly Media, Inc.". This book was released on 2018-01-04 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Software is eating the world, and GitHub is where software is built. GitHub is also a powerful way for people to collaborate on text-based documents, from contracts to screenplays to legislation. With this introductory guide, you'll learn how to use GitHub to manage and collaborate with developers, designers and other business professionals more effectively. Topics include project transparency, collaboration tools, the basics of Git version control management and how to make changes yourself - without having to bother your development team.
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.
Book Synopsis Introduction to 3D Game Programming with DirectX 12 by : Frank Luna
Download or read book Introduction to 3D Game Programming with DirectX 12 written by Frank Luna and published by Mercury Learning and Information. This book was released on 2016-04-19 with total page 900 pages. Available in PDF, EPUB and Kindle. Book excerpt: This updated bestseller provides an introduction to programming interactive computer graphics, with an emphasis on game development using DirectX 12. The book is divided into three main parts: basic mathematical tools, fundamental tasks in Direct3D, and techniques and special effects. It shows how to use new Direct12 features such as command lists, pipeline state objects, descriptor heaps and tables, and explicit resource management to reduce CPU overhead and increase scalability across multiple CPU cores. The book covers modern special effects and techniques such as hardware tessellation, writing compute shaders, ambient occlusion, reflections, normal and displacement mapping, shadow rendering, and character animation. Includes a companion DVD with code and figures. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected]. FEATURES: • Provides an introduction to programming interactive computer graphics, with an emphasis on game development using DirectX 12 • Uses new Direct3D 12 features to reduce CPU overhead and take advantage of multiple CPU cores • Contains detailed explanations of popular real-time game effects • Includes a DVD with source code and all the images (including 4-color) from the book • Learn advance rendering techniques such as ambient occlusion, real-time reflections, normal and displacement mapping, shadow rendering, programming the geometry shader, and character animation • Covers a mathematics review and 3D rendering fundamentals such as lighting, texturing, blending and stenciling • Use the end-of-chapter exercises to test understanding and provide experience with DirectX 12
Book Synopsis Introducing Python by : Bill Lubanovic
Download or read book Introducing Python written by Bill Lubanovic and published by "O'Reilly Media, Inc.". This book was released on 2019-11-06 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned. You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.
Book Synopsis Introducing Distributed Application Runtime (Dapr) by : Radoslav Gatev
Download or read book Introducing Distributed Application Runtime (Dapr) written by Radoslav Gatev and published by Apress. This book was released on 2021-09-04 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use this book to learn the Distributed Application Runtime (Dapr), a new event-driven runtime from Microsoft designed to help developers build microservices applications, using a palette of languages and frameworks that run everywhere: on-premises, in any cloud, and even on the edge. One of the most popular architectural patterns for implementing large, complex, distributed solutions is the microservices architectural style. Because solutions are composed of services based on various languages, frameworks, and platforms, the more complex and compartmentalized an application becomes, the more considerations a developer has to keep in mind. Much of the time this proves to be difficult. Introducing Distributed Application Runtime (Dapr) is your guide to achieving more with less through patterns. Part I of the book is about understanding microservices and getting up and running with Dapr, either on your machine or in any Kubernetes cluster. From there you are guided through the concepts of Dapr, how it works, and what it can do for you. You will wrap up with various ways to debug Dapr applications using Visual Studio Code locally, inside a container or Kubernetes. In Part II you will jump into the reusable patterns and practices, the building blocks of Dapr. You will go from service invocation, publish and subscribe, state management, resource bindings, and the Actor model to secrets; each building block is covered in detail in its own dedicated chapter. You will learn what Dapr offers from a functional perspective and also how you can leverage the three pillars of observability (logs, metrics, and traces) in order to gain insight into your applications. In Part III you will explore advanced concepts, including using middleware pipelines, integrating Dapr into web frameworks such as ASP.NET Core, or the runtimes of Azure Logic Apps and Azure Functions. The book features a multi-versed set of examples that cover not only the plain API of Dapr, but also the .NET SDK. Hence, most of the examples are in .NET 5, with a small number in JavaScript to exemplify the use of multiple languages. Examples show you how to securely use Dapr to leverage a variety of services in Microsoft Azure, including Azure Kubernetes Service, Azure Storage, Azure Service Bus, Azure Event Grid, Azure Key Vault, Azure Monitor, and Azure Active Directory among others. What You Will Learn Recognize the challenges and boundaries of microservices architecture Host Dapr inside a Kubernetes cluster or as a standalone process Leverage and use Dapr’s ready-to-use patterns and practices Utilize its HTTP/gRPC APIs Use Dapr with ASP.NET Core and in .NET applications (with or without the SDK) Implement observability for Dapr applications Secure Dapr applications Integrate Dapr with the runtime of Azure Logic Apps and Azure Functions Realize the full potential of Visual Studio Code by using the right extensions that will contribute to a better development experience Who This Book Is For Developers and architects who want to utilize a proven set of patterns to help easily implement microservices applications
Book Synopsis Python Data Science Handbook by : Jake VanderPlas
Download or read book Python Data Science Handbook written by Jake VanderPlas and published by "O'Reilly Media, Inc.". This book was released on 2016-11-21 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Book Synopsis Introducing Regular Expressions by : Michael Fitzgerald
Download or read book Introducing Regular Expressions written by Michael Fitzgerald and published by "O'Reilly Media, Inc.". This book was released on 2012-07-10 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you’re a programmer new to regular expressions, this easy-to-follow guide is a great place to start. You’ll learn the fundamentals step-by-step with the help of numerous examples, discovering first-hand how to match, extract, and transform text by matching specific words, characters, and patterns. Regular expressions are an essential part of a programmer’s toolkit, available in various Unix utlilities as well as programming languages such as Perl, Java, JavaScript, and C#. When you’ve finished this book, you’ll be familiar with the most commonly used syntax in regular expressions, and you’ll understand how using them will save you considerable time. Discover what regular expressions are and how they work Learn many of the differences between regular expressions used with command-line tools and in various programming languages Apply simple methods for finding patterns in text, including digits, letters, Unicode characters, and string literals Learn how to use zero-width assertions and lookarounds Work with groups, backreferences, character classes, and quantifiers Use regular expressions to mark up plain text with HTML5
Download or read book CUDA by Example written by Jason Sanders and published by Addison-Wesley Professional. This book was released on 2010-07-19 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: CUDA is a computing architecture designed to facilitate the development of parallel programs. In conjunction with a comprehensive software platform, the CUDA Architecture enables programmers to draw on the immense power of graphics processing units (GPUs) when building high-performance applications. GPUs, of course, have long been available for demanding graphics and game applications. CUDA now brings this valuable resource to programmers working on applications in other domains, including science, engineering, and finance. No knowledge of graphics programming is required—just the ability to program in a modestly extended version of C. CUDA by Example, written by two senior members of the CUDA software platform team, shows programmers how to employ this new technology. The authors introduce each area of CUDA development through working examples. After a concise introduction to the CUDA platform and architecture, as well as a quick-start guide to CUDA C, the book details the techniques and trade-offs associated with each key CUDA feature. You’ll discover when to use each CUDA C extension and how to write CUDA software that delivers truly outstanding performance. Major topics covered include Parallel programming Thread cooperation Constant memory and events Texture memory Graphics interoperability Atomics Streams CUDA C on multiple GPUs Advanced atomics Additional CUDA resources All the CUDA software tools you’ll need are freely available for download from NVIDIA. http://developer.nvidia.com/object/cuda-by-example.html
Book Synopsis Introducing Spring Framework by : Felipe Gutierrez
Download or read book Introducing Spring Framework written by Felipe Gutierrez and published by Apress. This book was released on 2014-07-04 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introducing Spring Framework is your hands-on guide to learning to build applications using the Spring Framework. The book uses a simple My Documents application that you will develop incrementally over the course of the book and covers: • How to programmatically configure the Spring container and beans • How to use annotations for dependency injection • How to use collections and custom types • How to customize and configure bean properties and bean lifecycle interfaces • How to handle metadata using XML, annotations, and the Groovy bean reader • How to use the new Spring Boot and Spring XD After reading this book, you will have all you need to start using the Spring Framework effectively.
Book Synopsis Introduction to Computation and Programming Using Python, second edition by : John V. Guttag
Download or read book Introduction to Computation and Programming Using Python, second edition written by John V. Guttag and published by MIT Press. This book was released on 2016-08-12 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
Book Synopsis A Programmer's Introduction to Mathematics by : Jeremy Kun
Download or read book A Programmer's Introduction to Mathematics written by Jeremy Kun and published by . This book was released on 2020-05-17 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Programmer's Introduction to Mathematics uses your familiarity with ideas from programming and software to teach mathematics. You'll learn about the central objects and theorems of mathematics, including graphs, calculus, linear algebra, eigenvalues, optimization, and more. You'll also be immersed in the often unspoken cultural attitudes of mathematics, learning both how to read and write proofs while understanding why mathematics is the way it is. Between each technical chapter is an essay describing a different aspect of mathematical culture, and discussions of the insights and meta-insights that constitute mathematical intuition. As you learn, we'll use new mathematical ideas to create wondrous programs, from cryptographic schemes to neural networks to hyperbolic tessellations. Each chapter also contains a set of exercises that have you actively explore mathematical topics on your own. In short, this book will teach you to engage with mathematics. A Programmer's Introduction to Mathematics is written by Jeremy Kun, who has been writing about math and programming for 10 years on his blog "Math Intersect Programming." As of 2020, he works in datacenter optimization at Google.The second edition includes revisions to most chapters, some reorganized content and rewritten proofs, and the addition of three appendices.
Book Synopsis Introducing Ethereum and Solidity by : Chris Dannen
Download or read book Introducing Ethereum and Solidity written by Chris Dannen and published by Apress. This book was released on 2017-03-16 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use Solidity and the Ethereum project – second only to Bitcoin in market capitalization. Blockchain protocols are taking the world by storm, and the Ethereum project, with its Turing-complete scripting language Solidity, has rapidly become a front-runner. This book presents the blockchain phenomenon in context; then situates Ethereum in a world pioneered by Bitcoin. See why professionals and non-professionals alike are honing their skills in smart contract patterns and distributed application development. You'll review the fundamentals of programming and networking, alongside its introduction to the new discipline of crypto-economics. You'll then deploy smart contracts of your own, and learn how they can serve as a back-end for JavaScript and HTML applications on the Web. Many Solidity tutorials out there today have the same flaw: they are written for “advanced” JavaScript developers who want to transfer their skills to a blockchain environment. Introducing Ethereum and Solidity is accessible to technology professionals and enthusiasts of all levels. You’ll find exciting sample code that can move forward real world assets in both the academic and the corporate arenas. Find out now why this book is a powerful gateway for creative technologists of all types, from concept to deployment. What You’ll Learn See how Ethereum (and other cryptocurrencies) work Compare distributed apps (dapps) to web apps Write Ethereum smart contracts in Solidity Connect Ethereum smart contracts to your HTML/CSS/JavaScript web applications Deploy your own dapp, coin, and blockchain Work with basic and intermediate smart contracts Who This Book Is For Anyone who is curious about Ethereum or has some familiarity with computer science Product managers, CTOs, and experienced JavaScript programmers Experts will find the advanced sample projects in this book rewarding because of the power of Solidity
Book Synopsis Probabilistic Machine Learning by : Kevin P. Murphy
Download or read book Probabilistic Machine Learning written by Kevin P. Murphy and published by MIT Press. This book was released on 2022-03-01 with total page 858 pages. Available in PDF, EPUB and Kindle. Book excerpt: A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory. This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the new book is accompanied by online Python code, using libraries such as scikit-learn, JAX, PyTorch, and Tensorflow, which can be used to reproduce nearly all the figures; this code can be run inside a web browser using cloud-based notebooks, and provides a practical complement to the theoretical topics discussed in the book. This introductory text will be followed by a sequel that covers more advanced topics, taking the same probabilistic approach.
