An Introduction To Statistical Learning With Applications In R - Info and Reading Options
By Gareth James

"An Introduction To Statistical Learning With Applications In R" was published by Springer-Verlag New York Inc. in 2013 and it has 426 pages.
“An Introduction To Statistical Learning With Applications In R” Metadata:
- Title: ➤ An Introduction To Statistical Learning With Applications In R
- Author: Gareth James
- Number of Pages: 426
- Publisher: Springer-Verlag New York Inc.
- Publish Date: 2013
“An Introduction To Statistical Learning With Applications In R” Subjects and Themes:
- Subjects: ➤ Statistics - Mathematical statistics - Mathematical models - Problems, exercises - R (Computer program language) - Statistical Models - Statistics as Topic - Statistik - R. - Statistical Theory and Methods - Statistics and Computing/Statistics Programs - Mathematical and Computational Physics Theoretical - Statistics, general
Edition Identifiers:
- The Open Library ID: OL26184759M - OL17581605W
- Online Computer Library Center (OCLC) ID: 1004563473
- Library of Congress Control Number (LCCN): 2013936251
- ISBN-13: 9781461471370
- All ISBNs: 9781461471370
AI-generated Review of “An Introduction To Statistical Learning With Applications In R”:
"An Introduction To Statistical Learning With Applications In R" Description:
The Open Library:
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, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
Read “An Introduction To Statistical Learning With Applications In R”:
Read “An Introduction To Statistical Learning With Applications In R” by choosing from the options below.
Search for “An Introduction To Statistical Learning With Applications In R” downloads:
Visit our Downloads Search page to see if downloads are available.
Borrow "An Introduction To Statistical Learning With Applications In R" Online:
Check on the availability of online borrowing. Please note that online borrowing has copyright-based limitations and that the quality of ebooks may vary.
- Is Online Borrowing Available: Yes
- Preview Status: borrow
- Check if available: The Open Library & The Internet Archive
Find “An Introduction To Statistical Learning With Applications In R” in Libraries Near You:
Read or borrow “An Introduction To Statistical Learning With Applications In R” from your local library.
- The WorldCat Libraries Catalog: Find a copy of “An Introduction To Statistical Learning With Applications In R” at a library near you.
Buy “An Introduction To Statistical Learning With Applications In R” online:
Shop for “An Introduction To Statistical Learning With Applications In R” on popular online marketplaces.
- Ebay: New and used books.