An Introduction to Statistical Learning with Applications in R, 2nd Edition - Springer Texts in Statistics

Publisher: Springer
Condition: New
ISBN-13: 9781071614174
Author: Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
Format: Hardcover

The second edition of An Introduction to Statistical Learning with Applications in R by James, Witten, Hastie and Tibshirani, published in hardcover by Springer in the Springer Texts in Statistics series.

The book presents the main supervised and unsupervised learning methods with the mathematics kept to what a reader with a basic statistics background can follow: linear and logistic regression, resampling and model selection, tree-based methods, support vector machines, unsupervised learning, and in this edition additional material including deep learning and survival analysis. Each chapter ends with R labs.

Used as the entry text for statistical learning and applied machine learning courses, and by analysts and data scientists teaching themselves the field.