An Introduction to Statistical Learning : with Applications in R - neues Buch
2009, ISBN: 9781071614181
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 … Mehr…
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An Introduction to Statistical Learning : with Applications in R - neues Buch
2009, ISBN: 9781071614181
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 … Mehr…
hive.co.uk No. 9781071614181. Versandkosten:Instock, Despatched same working day before 3pm, zzgl. Versandkosten. Details... |
2009, ISBN: 9781071614181
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 … Mehr…
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An Introduction to Statistical Learning - neues Buch
2021, ISBN: 9781071614181
An Introduction to Statistical Learning - with Applications in R. 2nd ed. 2021: ab 63.99 € eBooks > Sachthemen & Ratgeber > Computer & Internet Springer US eBook als pdf, Springer US
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An Introduction to Statistical Learning - neues Buch
ISBN: 9781071614181
An Introduction to Statistical Learning - with Applications in R: ab 63.99 € eBooks > Fachthemen & Wissenschaft > Mathematik Springer US eBook als pdf, Springer US
eBook.de Versandkosten:in stock, , , DE. (EUR 0.00) Details... |
An Introduction to Statistical Learning : with Applications in R - neues Buch
2009, ISBN: 9781071614181
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 … Mehr…
Aruna Pal:
An Introduction to Statistical Learning : with Applications in R - neues Buch2009, ISBN: 9781071614181
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 … Mehr…
2009
ISBN: 9781071614181
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 … Mehr…
An Introduction to Statistical Learning - neues Buch
2021, ISBN: 9781071614181
An Introduction to Statistical Learning - with Applications in R. 2nd ed. 2021: ab 63.99 € eBooks > Sachthemen & Ratgeber > Computer & Internet Springer US eBook als pdf, Springer US
An Introduction to Statistical Learning - neues Buch
ISBN: 9781071614181
An Introduction to Statistical Learning - with Applications in R: ab 63.99 € eBooks > Fachthemen & Wissenschaft > Mathematik Springer US eBook als pdf, Springer US
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Detailangaben zum Buch - Introduction to Statistical Learning
EAN (ISBN-13): 9781071614181
Erscheinungsjahr: 2009
Herausgeber: Springer US
Buch in der Datenbank seit 2021-05-25T20:56:28+02:00 (Berlin)
Detailseite zuletzt geändert am 2024-04-05T18:13:32+02:00 (Berlin)
ISBN/EAN: 9781071614181
ISBN - alternative Schreibweisen:
978-1-0716-1418-1
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: james gareth
Titel des Buches: introduction statistical learning
Daten vom Verlag:
Autor/in: Gareth James; Daniela Witten; Trevor Hastie; Robert Tibshirani
Titel: Springer Texts in Statistics; An Introduction to Statistical Learning - with Applications in R
Verlag: Springer; Springer US
607 Seiten
Erscheinungsjahr: 2021-07-29
New York; NY; US
Sprache: Englisch
64,19 € (DE)
66,00 € (AT)
71,00 CHF (CH)
Available
XV, 607 p. 191 illus., 182 illus. in color.
EA; E107; eBook; Nonbooks, PBS / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; R; R software; data mining; inference; statistical learning; supervised learning; unsupervised learning; B; Statistical Theory and Methods; Statistics and Computing; Artificial Intelligence; Statistics; Mathematics and Statistics; Mathematische und statistische Software; Künstliche Intelligenz; BB
Preface.- 1 Introduction.- 2 Statistical Learning.- 3 Linear Regression.- 4 Classification.- 5 Resampling Methods.- 6 Linear Model Selection and Regularization.- 7 Moving Beyond Linearity.- 8 Tree-Based Methods.- 9 Support Vector Machines.- 10 Deep Learning.- 11 Survival Analysis and Censored Data.- 12 Unsupervised Learning.- 13 Multiple Testing.- Index.Presents an essential statistical learning toolkit for practitioners in science, industry, and other fields Demonstrates application of the statistical learning methods in R Includes new chapters on deep learning, survival analysis, and multiple testing Covers a range of topics, such as linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and deep learning Features extensive color graphics for a dynamic learning experience Includes supplementary material: sn.pub/extras
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