• Build automated modules for different machine learning components
• Understand each component of a machine learning pipeline in depth
• Learn to use different open source...

Based on the author’s course at NYU, Linear Algebra and Probability for Computer Science Applications gives an introduction to two mathematical fields that are fundamental in many areas of computer science. The course and the text are addressed to students with a very weak mathematical background. Most of the...

Discover how C's efficiency makes it a popular choice in a wide variety of applications and operating systems with special applicability to wearables, game programming, system level programming, embedded device/firmware programming and in Arduino and related electronics hobbies in this condensed code and syntax guide. This book...

• Get a hands-on, fast-paced introduction to the Python data science stack
• Explore ways to create useful metrics and statistics from...

Suitable for a compact course or self-study, Computational Statistics: An Introduction to R illustrates how to use the freely available R software package for data analysis, statistical programming, and graphics. Integrating R code and examples throughout, the text only requires basic knowledge of statistics and...

• A hands-on guide to web scraping using Python with solutions to real-world problems
• Create a number of different web scrapers in Python to extract information
• This book...

In this follow up work to the best selling Beginning iPhone Development with Swift, you’ll learn how to improve your apps by managing the performance of your programs using...

Mastering Windows Server 2016 is a complete resource for IT professionals needing to get quickly up to date on the latest release. Designed to provide comprehensive information in the context of real-world usage, this book offers expert guidance through the new...