An Introduction to Statistical Learning with Applications in Python

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, marketing, and astrophysics in the past twenty years. Thi...

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Bibliographic Details
Main Authors: James, Gareth, Witten, Daniela (Author), Hastie, Trevor (Author), Tibshirani, Robert (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2023, 2023
Edition:1st ed. 2023
Series:Springer Texts in Statistics
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Introduction
  • Statistical Learning
  • Linear Regression
  • Classification
  • Resampling Methods
  • Linear Model Selection and Regularization
  • Moving Beyond Linearity
  • Tree-Based Methods
  • Support Vector Machines
  • Deep Learning
  • Survival Analysis and Censored data
  • Unsupervised Learning
  • Multiple Testing
  • Index