TY  - BOOK
AU  - James, Gareth 
AU  - Witten,Daniela
AU  - Hastie,Trevor
AU  - Tibshirani,Robert
TI  - An introduction to statistical learning : : with applications in  python / by 
SN  - 9783031391897
U1  - 519.50285 T23 
PY  - 2023///
CY  - Switzerland : 
PB  - Springer, 
KW  - Mathematical statistics
KW  - Mathematical models
KW  - Computer program language
KW  - Statistics
N1  - Includes index
N2  - 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. - Taken from publisher's website
ER  -