An Introduction to Statistical Learning: with Applications in Python (Springer Texts in Statistics)

I've studied the ESL and ISLR since they've been published; I've used ISLR as a text to teach graduate level courses and also as my guide to design a course called "Mathematics for Data Scientists" for a Master's program of a well-known University in Chicago. There's not much to say about the older editions (the precursors to this one) other that 'excellent'.About this new edition, ISLP: (1) The new chapters were wisely chosen to reflect current practice, e.g., Neural Networks. Also, the updates on older chapters is very well-done, keeping with newer terminology and better explanations; (2) The introduction of Python is, of course, a very welcome update, indeed.I have one negative comment, which has nothing to do with the content (hence my five-star review), but rather with the book binding itself. This is only relevant to the PAPERBACK edition, not the regular hardcover. It falls apart easily. After only a couple of months of use, pages are coming right off. This is very disappointing for a serious printing house like Springer. I've owned and used paperbacks of similar size heavily and for years and they are fine. With all due respect to Springer, but i feel they did a disservice to the authors and the community.All in all, highly recommended, but maybe avoid the paperback edition.

The quality is very good; printing is super clear. Anyway, this is the best machine learning text book you should have. They added deep learning in this version, and the python codes are great.

Okay, so the Python code is dated and not well explained, but it is the bible for statistics of machine learning for programmers

This is not a content review but about the bookbinding and printing quality. Like other reviewers have noted, the binding is awful. Page 1 is about to break at any moment the time I opened the book. For a Springer hardcover, I expect acid-free paper like the related book "The Elements of Statistical Learning" I bought before, but this book is printed on regular low-cost paper. It does not look like a genuine Springer hardcover book. Many Amazon paperback books are printed in local printing shops at low cost. I feel this shady practice is now extended to hardcover. I requested a replacement.

Excelente libroMuy buenos temas y con gran profundidad

I purchased this book for self study, with the authors’ video in YouTube, I really enjoyed the book .

This book is well written. The authors have a deep knowledge of the Applied Statistics. I bought the version for R, I am enjoying the book so much I downloaded the version for Python. I am very grateful for such works. Take care.

2023-08-04:I received the hardcover edition, which I ordered directly from Springer. This is a high quality book with color visualizations and easy to read code blocks.2023-07-17:I'm super excited to order the hardcover version of this textbook for stats with python (when it become available again). I also have the previous two versions for R, though I don't love R. One author, Gareth James, posted a link to "statlearning dot com" for textbook resources, and errata. The resources include Jupyter notebooks, chapter slides, data sets, and figures.This is a really great text (I currently have the PDF version), with many supporting resources.The publisher, Springer Link, shows the hardcover price as $109.99, so don't indulge unscrupulous resellers trying to gouge you for more than that.