An Introduction to Statistical Learning with Applications in R
An introduction to statistical learning methods, this book contains a number of R labs with detailed explanations on how to implement the various methods in real life settings.
Tag(s): Machine Learning R Statistics
Publication date: 24 Jun 2014
ISBN-10: 1461471370
ISBN-13: 9781461471370
Paperback: 440 pages
Views: 23,223
An Introduction to Statistical Learning with Applications in R
An introduction to statistical learning methods, this book contains a number of R labs with detailed explanations on how to implement the various methods in real life settings.
Publication date: 24 Jun 2014
ISBN-10: 1461471370
ISBN-13: 9781461471370
Paperback: 440 pages
Views: 23,223
Document Type: N/A
Publisher: Springer-Verlag GmbH
License: n/a
Post time: 08 Apr 2016 12:00:00
This book provides an introduction to statistical learning methods. It is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences. The book also contains a number of R labs with detailed explanations on how to implement the various methods in real life settings, and should be a valuable resource for a practicing data scientist.
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About The Author(s)
Trevor Hastie is The John A. Overdeck Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University.
Trevor Hastie is The John A. Overdeck Professor, Professor of Statistics, and Professor of Biomedical Data Science at Stanford University.
No information is available for this author.
Robert Tibshirani is a Professor of Health Research and Policy, and Statistics at Stanford University.
Robert Tibshirani is a Professor of Health Research and Policy, and Statistics at Stanford University.
No information is available for this author.