An Introduction to Statistical Learning provides a broad and less technical treatment of key topics in statistical learning. This book is appropriate for anyone who wishes to use contemporary …

The course for An Introduction to Statistical Learning, with Applications in R (Second Edition) is available here. This popular course has been taken by over 290,000 learners as of November …

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Inspired by "The Elements of Statistical Learning'' (Hastie, Tibshirani and Friedman), this book provides clear and intuitive guidance on how to implement cutting edge statistical and machine …

The original Chapter 10 lab made use of keras, an R package for deep learning that relies on Python. Getting keras to work on your computer can be a bit of a challenge.

R Materials Get the R package. Chapter 2 .R File Chapter 3 .R File Chapter 4 .R File Chapter 5 .R File Chapter 6 .R File Chapter 7 .R File Chapter 8 .R File Chapter 9 .R File Chapter 10 .R File …

Nov 1, 2025 · I’ve been studying the English PDF version from the official website, but since many students in Latin America use this book, a Spanish version would be incredibly helpful for …

This book is appropriate for anyone who wishes to use contemporary tools for data analysis. The book has been translated into Chinese, Italian, Japanese, Korean, Mongolian, Russian and …

On page 443: immediately before Section 10.1, we plan to add the following text in the next printing: “Since the first printing of this book, the torch package has become available as an …

On the bottom of page 81, the sentence “Any statistical software package can be used to compute these coefficient estimates, and later in this chapter we will show how this can be done in R.” …