an Introduction to Statistical Learning

An Introduction to Statistical Learning: with Applications in R (Corrected at 8th printing 2017)

An Introduction to Statistical Learning: with Applications in R by Gareth James
English | PDF,EPUB (True) | 2013 (Corrected at 8th printing 2017) | 434 Pages | ISBN : 1461471370 | 14.62 MB

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.

An Introduction to Statistical Learning: with Applications in R (Repost)  eBooks & eLearning

Posted by advisors at Sept. 3, 2014
An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R By Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
2014 | 426 Pages | ISBN: 1461471370 | PDF | 11 MB

An Introduction to Statistical Learning: with Applications in R  eBooks & eLearning

Posted by tarantoga at Feb. 15, 2017
An Introduction to Statistical Learning: with Applications in R

Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, "An Introduction to Statistical Learning: with Applications in R"
ISBN: 1461471370 | 2013 | EPUB | 426 pages | 4 MB

An Introduction to Statistical Learning: with Applications in R (Repost)  eBooks & eLearning

Posted by enmoys at Nov. 1, 2014
An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R By Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
2014 | 426 Pages | ISBN: 1461471370 | PDF | 11 MB

An Introduction to Statistical Learning: with Applications in R (Repost)  eBooks & eLearning

Posted by insetes at Oct. 17, 2017
An Introduction to Statistical Learning: with Applications in R (Repost)

An Introduction to Statistical Learning: with Applications in R By Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
2014 | 426 Pages | ISBN: 1461471370 | PDF | 11 MB

An Introduction to Statistical Learning: with Applications in R  eBooks & eLearning

Posted by bookwyrm at June 29, 2014
An Introduction to Statistical Learning: with Applications in R

An Introduction to Statistical Learning: with Applications in R By Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
2014 | 426 Pages | ISBN: 1461471370 | PDF | 11 MB

A Solution Manual and Notes for: An Introduction to Statistical Learning  eBooks & eLearning

Posted by Grev27 at March 25, 2019
A Solution Manual and Notes for: An Introduction to Statistical Learning

John Weatherwax, "A Solution Manual and Notes for: An Introduction to Statistical Learning"
English | ASIN: B00JODN038 | 2014 | EPUB | 140 pages | 1 MB

An Introduction to Statistical Learning, 2nd Edition  eBooks & eLearning

Posted by hill0 at July 30, 2021
An Introduction to Statistical Learning, 2nd Edition

An Introduction to Statistical Learning: with Applications in R
English | 2021 | ISBN: 1071614177 | 616 Pages | PDF | 14 MB

An Introduction to Statistical Learning: With Applications in Python  eBooks & eLearning

Posted by hill0 at July 2, 2023
An Introduction to Statistical Learning: With Applications in Python

An Introduction to Statistical Learning: With Applications in Python
English | 2023 | ISBN: 3031391896 | 617 Pages | PDF (True) | 13 MB
Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R

Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R by Daniel D. Gutierrez
English | 18 Sept. 2015 | ISBN: 1634620968 | 282 Pages | True AZW3 (Kindle)/(EPUB/PDF conv) | 15.44 MB

A practitioner's tools have a direct impact on the success of his or her work. This book will provide the data scientist with the tools and techniques required to excel with statistical learning methods in the areas of data access, data munging, exploratory data analysis, supervised machine learning, unsupervised machine learning and model evaluation.