Introduction to Statistical Learning: With Applications in R is a comprehensive textbook exploring topics in computers, mathematics, and statistical software. Published by Springer New York in 2017, this book offers a detailed introduction to statistical learning methods with a focus on R programming. Written by authors Trevor Hastie, Gareth James, Robert Tibshirani, and Daniela Witten, this hardcover textbook is a valuable resource for students and professionals interested in mathematical and statistical software, probability and statistics, and artificial intelligence and semantics. With 426 pages and a series of informative examples and exercises, this textbook provides a thorough introduction to the field of statistical learning.