Introduction to Statistical Learning

Overview of Supervised Learning

Linear Methods for Regression

Linear Methods for Classification

Basis Expansions and Regularization

Kernel Smoothing Methods

Model Assessment and Selection

Boosting and Additive Trees

Neural Networks and Support Vector Machines

Unsupervised Learning

The Elements of Statistical Learning provides a comprehensive introduction to statistical learning, data mining, inference, and prediction. This book presents a range of methods and applications of the concepts, offering a unified, conceptual treatment of statistical models and the abstraction of large data sets into interpretable knowledge.

science

non_fiction

The Elements of Statistical Learning: Data Mining, Inference, and Prediction