Mathematics and Programming for Machine Learning with R: From the Ground Up

Mathematics and Programming for Machine Learning with R: From the Ground Up is a book that teaches novice programmers how to implement machine learning algorithms in R. It covers fundamental computer and mathematical concepts, probability-based machine learning algorithms, and machine learning based on artificial neural networks. The book includes more than 400 exercises and a strong emphasis on improving programming skills.

Format: Paperback / softback
Length: 408 pages
Publication date: 27 October 2020
Publisher: Taylor & Francis Ltd

Based on the author's extensive experience in teaching data science for over a decade, Mathematics and Programming for Machine Learning with R: From the Ground Up offers a comprehensive guide to understanding and implementing machine learning algorithms using the R programming language. The book aims to provide readers with a deep understanding of the underlying principles and techniques behind machine learning, as well as the practical skills required to program them. Written with novice programmers in mind, the book progresses step-by-step, covering fundamental computer and mathematical concepts such as logic, sets, and probability before delving into powerful deep learning algorithms.

The first eight chapters focus on probability-based machine learning algorithms, while the latter eight chapters explore machine learning based on artificial neural networks. The book assumes a basic familiarity with probability and statistics, although the second half assumes the reader has a foundational understanding of calculus. Throughout the text, the author emphasizes improving programming skills and guiding beginners toward the implementation of full-fledged algorithms.

Key highlights of the book include:

Over 400 carefully designed exercises to reinforce learning and practice.
A strong emphasis on improving programming skills and guiding beginners toward the implementation of complex algorithms.
Comprehensive coverage of fundamental computer and mathematical concepts, including logic, sets, and probability.
In-depth explanations of machine learning algorithms, their principles, and their applications in various fields.
Examples and case studies drawn from real-world scenarios to illustrate the practical implications of machine learning.
Access to a companion website with additional resources, code examples, and lecture slides.
Whether you are a novice programmer looking to foray into the world of machine learning or a seasoned data scientist seeking to enhance your skills, Mathematics and Programming for Machine Learning with R: From the Ground Up is an invaluable resource. With its clear and concise writing style, extensive exercises, and practical examples, this book provides a solid foundation for anyone interested in developing machine learning solutions with R.

Weight: 798g
Dimension: 177 x 253 x 28 (mm)
ISBN-13: 9780367507855