Price: $79.99 – $49.95
(as of Jan 05,2025 02:46:51 UTC – Details)
Publisher : SPRINGER; 1st edition (January 1, 2013)
Language : English
Hardcover : 426 pages
ISBN-10 : 1461471370
ISBN-13 : 978-1461471370
Item Weight : 2.31 pounds
Dimensions : 6.1 x 1 x 9.3 inches
Customers say
Customers find the book provides the right amount of theory and practice. They appreciate the helpful R code examples and comprehensive coverage of statistical learning. The book is praised for its affordability and visual quality, with well-illustrated figures and diagrams that aid visualization. Many customers consider it a useful resource for gaining an understanding of the principles and getting started with R.
AI-generated from the text of customer reviews
Have you ever wanted to learn about statistical learning and its applications in R? Look no further than “An Introduction to Statistical Learning: with Applications in R” by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani. This comprehensive textbook, part of the Springer Texts in Statistics series, provides a practical introduction to the field of statistical learning, covering topics such as linear regression, classification, resampling methods, tree-based methods, and more.
The book is designed for students and practitioners who are interested in learning how to analyze and interpret data using statistical methods. It includes numerous examples and exercises to help readers gain a better understanding of the concepts presented. Additionally, the book includes R code throughout, allowing readers to replicate the analyses and experiments discussed in the text.
Whether you are a beginner looking to learn the basics of statistical learning or a seasoned practitioner looking to expand your knowledge, “An Introduction to Statistical Learning: with Applications in R” is a valuable resource that will help you master the fundamentals of statistical learning. So, grab your copy today and start your journey into the exciting world of statistical learning!
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