An Introduction to Statistical Learning with Applications in R


Title:  An Introduction to Statistical Learning with Applications in R

Authors: Gareth James

Daniela Witten

Trevor Hastie

Robert Tibscirani

License: N/A

Book Description:

Statistical learning refers to a set of tools for modeling and understanding complex data sets. It is a recently developed area in statistics and blends with parallel developments in computer science and, in particular, machine learning.

The field encompasses many methods such as the lasso and sparse regression, classification and regression trees, and boosting and support vector machines. With the explosion of “Big Data” problems, statistical learning has become a very hot field in many scientific areas as well as marketing, finance, and other business disciplines.

People with statistical learning skills are in high demand. This book is appropriate for advanced undergraduates or master’s students in statistics or related quantitative fields or for individuals in other disciplines who wish to use statistical learning tools to analyze their data.

It can be used as a textbook for a course spanning one or two semesters.

An Introduction to Statistical Learning with Applications in R
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