Programming in Lua


Roberto Ierusalimschy - 2001
    Currently, Lua is being used in areas ranging from embedded systems to Web development and is widely spread in the game industry, where knowledge of Lua is an indisputable asset. "Programming in Lua" is the official book about the language, giving a solid base for any programmer who wants to use Lua. Authored by Roberto Ierusalimschy, the chief architect of the language, it covers all aspects of Lua 5---from the basics to its API with C---explaining how to make good use of its features and giving numerous code examples. "Programming in Lua" is targeted at people with some programming background, but does not assume any prior knowledge about Lua or other scripting languages. This Second Edition updates the text to Lua 5.1 and brings substantial new material, including numerous new examples, a detailed explanation of the new module system, and two new chapters centered on multiple states and garbage collection.

The C# Programming Yellow Book


Rob Miles - 2010
    With jokes, puns, and a rigorous problem solving based approach. You can download all the code samples used in the book from here: http://www.robmiles.com/s/Yellow-Book...

Team Topologies: Organizing Business and Technology Teams for Fast Flow


Matthew Skelton - 2019
    But how do you build the best team organization for your specific goals, culture, and needs? Team Topologies is a practical, step-by-step, adaptive model for organizational design and team interaction based on four fundamental team types and three team interaction patterns. It is a model that treats teams as the fundamental means of delivery, where team structures and communication pathways are able to evolve with technological and organizational maturity.In Team Topologies, IT consultants Matthew Skelton and Manuel Pais share secrets of successful team patterns and interactions to help readers choose and evolve the right team patterns for their organization, making sure to keep the software healthy and optimize value streams.Team Topologies is a major step forward in organizational design for software, presenting a well-defined way for teams to interact and interrelate that helps make the resulting software architecture clearer and more sustainable, turning inter-team problems into valuable signals for the self-steering organization.

Java Generics and Collections: Speed Up the Java Development Process


Maurice Naftalin - 2006
    Generics and the greatly expanded collection libraries have tremendously increased the power of Java 5 and Java 6. But they have also confused many developers who haven't known how to take advantage of these new features.Java Generics and Collections covers everything from the most basic uses of generics to the strangest corner cases. It teaches you everything you need to know about the collections libraries, so you'll always know which collection is appropriate for any given task, and how to use it.Topics covered include:• Fundamentals of generics: type parameters and generic methods• Other new features: boxing and unboxing, foreach loops, varargs• Subtyping and wildcards• Evolution not revolution: generic libraries with legacy clients and generic clients with legacy libraries• Generics and reflection• Design patterns for generics• Sets, Queues, Lists, Maps, and their implementations• Concurrent programming and thread safety with collections• Performance implications of different collectionsGenerics and the new collection libraries they inspired take Java to a new level. If you want to take your software development practice to a new level, this book is essential reading.Philip Wadler is Professor of Theoretical Computer Science at the University of Edinburgh, where his research focuses on the design of programming languages. He is a co-designer of GJ, work that became the basis for generics in Sun's Java 5.0.Maurice Naftalin is Technical Director at Morningside Light Ltd., a software consultancy in the United Kingdom. He has most recently served as an architect and mentor at NSB Retail Systems plc, and as the leader of the client development team of a major UK government social service system."A brilliant exposition of generics. By far the best book on the topic, it provides a crystal clear tutorial that starts with the basics and ends leaving the reader with a deep understanding of both the use and design of generics." Gilad Bracha, Java Generics Lead, Sun Microsystems

Getting Real: The Smarter, Faster, Easier Way to Build a Web Application


37 Signals - 2006
    At under 200 pages it's quick reading too. Makes a great airplane book.

The Architecture of Open Source Applications


Amy Brown - 2011
    In contrast, most software developers only ever get to know a handful of large programs well—usually programs they wrote themselves—and never study the great programs of history. As a result, they repeat one another's mistakes rather than building on one another's successes.This book's goal is to change that. In it, the authors of twenty-five open source applications explain how their software is structured, and why. What are each program's major components? How do they interact? And what did their builders learn during their development? In answering these questions, the contributors to this book provide unique insights into how they think.If you are a junior developer, and want to learn how your more experienced colleagues think, this book is the place to start. If you are an intermediate or senior developer, and want to see how your peers have solved hard design problems, this book can help you too.

The Docker Book: Containerization is the new virtualization


James Turnbull - 2014
    In this book, we'll will walk you through installing, deploying, managing, and extending Docker. We're going to do that by first introducing you to the basics of Docker and its components. Then we'll start to use Docker to build containers and services to perform a variety of tasks. We're going to take you through the development life cycle, from testing to production, and see where Docker fits in and how it can make your life easier. We'll make use of Docker to build test environments for new projects, demonstrate how to integrate Docker with continuous integration workflow, and then how to build application services and platforms. Finally, we'll show you how to use Docker's API and how to extend Docker yourself. We'll teach you how to: * Install Docker. * Take your first steps with a Docker container. * Build Docker images. * Manage and share Docker images. * Run and manage more complex Docker containers. * Deploy Docker containers as part of your testing pipeline. * Build multi-container applications and environments. * Explore the Docker API. * Getting Help and Extending Docker.

Reinforcement Learning: An Introduction


Richard S. Sutton - 1998
    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.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 when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

Machine Learning for Hackers


Drew Conway - 2012
    Authors Drew Conway and John Myles White help you understand machine learning and statistics tools through a series of hands-on case studies, instead of a traditional math-heavy presentation.Each chapter focuses on a specific problem in machine learning, such as classification, prediction, optimization, and recommendation. Using the R programming language, you'll learn how to analyze sample datasets and write simple machine learning algorithms. "Machine Learning for Hackers" is ideal for programmers from any background, including business, government, and academic research.Develop a naive Bayesian classifier to determine if an email is spam, based only on its textUse linear regression to predict the number of page views for the top 1,000 websitesLearn optimization techniques by attempting to break a simple letter cipherCompare and contrast U.S. Senators statistically, based on their voting recordsBuild a "whom to follow" recommendation system from Twitter data