An introduction to statistical learning : with applications in Python / Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshiran, Jonathan Taylor.
Material type:
TextSeries: [Springer texts in statistics]Publication details: Switzerland : Springer Nature , c2023.Description: xv, 607p. : ill. col. ; 24 cmISBN: - 9783031387463
- 519.5 INT
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CPGS | 519.5 INT (Browse shelf(Opens below)) | Not For Loan | CPGS6228 | ||
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CPGS | 519.5 INT(2) (Browse shelf(Opens below)) | 2 | Available | CPGS6229 |
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| 519.5 GUP;46 Statistical methods / | 519.5 GUP;46(2) Statistical methods / | 519.5 GUP(5) Statistical methods / | 519.5 INT An introduction to statistical learning : with applications in Python / | 519.5 INT(2) An introduction to statistical learning : with applications in Python / | 519.5 KUS Basic concepts in statistics / | 519.5 KUS(2) Basic concepts in statistics / |
The 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..etc.. (Back cover information)
Includes index.
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