An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform.Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naïve Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.
✔ Author(s): Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
✔ Title: An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
✔ Rating : 4.6 out of 5 base on (266 reviews)
✔ ISBN-10: 1071614207
✔ ISBN-13: 9781071614204
✔ Language: English
✔ Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
✔ Device compatibles: Android, iOS, PC and Amazon Kindle
Readers' opinions about An Introduction to Statistical Learning by Gareth James
Beata Shepard
I'm still in awe of the intricate plot and the way everything seamlessly came together. The twists kept me guessing until the very end. It's one of those rare books that leave a lasting impact.
Josephine Alvarez
The author's writing style is so captivating; I couldn't put the book down. Every sentence was beautifully crafted, and the descriptions painted vivid images in my mind. A true literary gem.
Rosa Bax
The author's ability to evoke a wide range of emotions through their words is truly remarkable. I felt like I was on an emotional rollercoaster throughout the entire book.
