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An Introduction to Statistical Learning: with Applications in R Hardcover – July 30 2021
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"An Introduction to Statistical Learning (ISL)" by James, Witten, Hastie and Tibshirani is the "how to'' manual for statistical learning. 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 learning methods. ISL makes modern methods accessible to a wide audience without requiring a background in Statistics or Computer Science. The authors give precise, practical explanations of what methods are available, and when to use them, including explicit R code. Anyone who wants to intelligently analyze complex data should own this book." (Larry Wasserman, Professor, Department of Statistics and Machine Learning Department, Carnegie Mellon University)
From the Back Cover
- Publisher : Springer; 2nd ed. 2021 edition (July 30 2021)
- Language : English
- Hardcover : 607 pages
- ISBN-10 : 1071614177
- ISBN-13 : 978-1071614174
- Item weight : 1.19 kg
- Dimensions : 20.32 x 3.05 x 23.88 cm
- Best Sellers Rank: #65,478 in Books (See Top 100 in Books)
- #15 in AI Computer Mathematics
- #19 in Mathematical & Statistical Software (Books)
- #20 in AI Theory of Computing
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Bought it for a Masters course but provides a lot of background for business analytics as well
I already knew most of the concepts but became hooked because of how clear the explanations are. The authors convey complex ideas with remarkable simplicity, and for that, I think this is the most important book for data scientists.
I am an avid opposer of the R programming language (ew) and even I enjoyed the applied programming parts of the book.
In all honesty, the applications in R are very good, but it's not the main focus of the book. I think people should read this to understand the inner workings of the most popular AI algorithms instead of learning how to train predictive models (especially in R, haha).
Overall, I think this is a great book for beginners and veterans alike. I would not hesitate to recommend this book to anyone interested in statistics, data and AI.