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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani




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 | #3792 in Books |  Springer |  2017-09-01 | Original language:English | PDF # 1 |  1.00 x6.40 x9.40l,2.00 | File type: PDF | 426 pages

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||232 of 237 people found the following review helpful.| wonderful but watch the movie|By I Teach Typing|This is a wonderful book written by luminaries in the field. While it is not for casual consumption, it is a relatively approachable review of the state of the art for people who do not have the hardcore math needed for The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Seri| |Poullis, Computing s, September, 2014)|“The book provides a good introduction to R. The code for all the statistical methods introduced in the book is carefully explained. … the book will certainly be useful to many people (including me). I will

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, re...

You easily download any file type for your device.An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)   |  Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani. Just read it with an open mind because none of us really know.

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