Found 668 books
Machine Learning in Sports

This book provides cutting-edge work on machine learning in sports analytics, emphasizing the integration of computer vision, data analytics, and machine learning to redefine strategic sports analysis. This book not only covers the essential methodologies of capturing and analyzing real sports data but also pioneers the integration of real-world analytics with digital modeling, advancing

The Haskell School of Music

This free book explores the fundamentals of computer music and functional programming through the Haskell programming language. Functional programming is typically considered difficult to learn. This introduction in the context of creating music will allow students and professionals with a musical inclination to leverage their experience to help understand concepts that might be intimida

Physical Modeling in MATLAB, 4th Edition

Modeling and simulation are powerful tools for explaining the world, making predictions, designing things that work, and making them work better. Learning to use these tools can be difficult; this book is my attempt to make the experience as enjoyable and productive as possible. By reading this book - and working on the exercises - you will learn some programming, some modeling, and some

The Design and Implementation of the Anykernel and Rump Kernels, 2nd Edition

The mission of the first edition of this book was to introduce the anykernel and rump kernels and motivate their existence. Additionally, we explored the characteristics of the technology through various experiments. The paramount, often criminally overlooked experiment was the one hiding in plain sight: is it possible to construct the system in a sustainable, real-world compatible fashi

Learn BlackBerry 10 App Development

Learn how to leverage the BlackBerry 10 Cascades framework to create rich native applications. Learn BlackBerry 10 App Development gives you a solid foundation for creating BlackBerry 10 apps efficiently. Along the way, you will learn how to use QML and JavaScript for designing your app's UI, and C++/Qt for the application logic. No prior knowledge of C++ is assumed and the book covers t

Mercurial: The Definitive Guide

This instructive book takes you step by step through ways to track, merge, and manage both open source and commercial software projects with Mercurial, using Windows, Mac OS X, Linux, Solaris, and other systems. Mercurial is the easiest system to learn when it comes to distributed revision control. And it's a very flexible tool that's ideal whether you're a lone programmer working on a s

CouchDB: The Definitive Guide

Three of CouchDB's creators show you how to use this document-oriented database as a standalone application framework or with high-volume, distributed applications. With its simple model for storing, processing, and accessing data, CouchDB is ideal for web applications that handle huge amounts of loosely structured data. That alone would stretch the limits of a relational database, yet C

You Don't Know JS Yet: Scope and Closures, 2nd Edition

The worldwide best selling You Don't Know JS book series is back for a 2nd edition: You Don't Know JS Yet. All 6 books are brand new, rewritten to cover all sides of JS for 2020 and beyond. You'll still get in-depth coverage of the core language, applied in useful code organization patterns for your programs. And of course, through Kyle's unique perspective and conversational tone, explo

Test-Driven Development with Python

By taking you through the development of a real web application from beginning to end, this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You'll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. The result? Clean code that works. In the proc

R for Data Science

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors