Computing & Internet Programming Books

Ry's Git Tutorial

Git is a free version control system known for its speed, reliability, and non-linear development model. Its popularity among open-source developers makes Git a necessary tool for professional programmers, but it can also do wonders for your personal coding workflow. You’ll be able to experiment with new ideas, radically refactor existing code, and efficiently share changes with other developers—all without the slightest worry towards breaking your project.This comprehensive guide will walk you through the entire Git library, writing code and executing commands every step of the way. You'll create commits, revert snapshots, navigate branches, communicate with remote repositories, and experience core Git concepts first-hand.Designed for newcomers to distributed development, Ry's Git Tutorial presents this complex subject in simple terms that anyone can understand. Beginner and veteran programmers alike will find this book to be a fun, fast, and friendly introduction to Git-based revision control.

An Introduction to APIs

Have you ever wondered how Facebook is able to automatically display your Instagram photos? How about how Evernote syncs notes between your computer and smartphone? If so, then it’s time to get excited!In this book, we walk you through what it takes for companies to link their systems together. We start off easy, defining some of the tech lingo you may have heard before, but didn’t fully understand. From there, each lesson introduces something new, slowly building up to the point where you are confident about what an API is and, for the brave, could actually take a stab at using one.

Automated Machine Learning: Methods, Systems, Challenges (The Springer Series on Challenges in Machine Learning)

This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work. 

Programming for Computations - Python: A Gentle Introduction to Numerical Simulations with Python (Texts in Computational Science and Engineering Book 15)

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.

Introduction to R Programming (101 Non-Fiction Series Book 7)

This book is part of a series that includes MBA Core & Elective coursework taught at prestigious universities like Harvard and Wharton. The series consists of Core & Elective courses that stemmed from more than ten years of professional experience in Wall Street and Startups. The elective courses introduce Machine Learning, Python, Blockchain and Cryptocurrencies, Communications skills, R language, Excel advanced features, PowerPoint advanced features, interview questions, and more