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- 607 pages
- 22 hours of reading
More about the book
Focusing on the principles of statistical learning, this book provides a comprehensive overview of key concepts and techniques used in data analysis. It emphasizes practical applications and includes real-world examples to illustrate methods such as regression, classification, and resampling. Designed for readers with a background in statistics and some programming knowledge, it balances theoretical foundations with hands-on exercises, making it an essential resource for anyone looking to deepen their understanding of statistical modeling and machine learning.
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An Introduction to Statistical Learning, Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
- Language
- Released
- 2021
- product-detail.submit-box.info.binding
- (Hardcover)
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- Subtitle
- with Applications in R
- Language
- English
- Publisher
- Springer-Verlag GmbH
- Released
- 2021
- Format
- Hardcover
- Pages
- 607
- ISBN13
- 9781071614174
- Series
- Tags
- Non-Fiction, Textbooks, Technology & Engineering, Computers & Internet, Science, Technology, Math Textbooks
- Rating
- 4.6 out of 5
- Description
- Focusing on the principles of statistical learning, this book provides a comprehensive overview of key concepts and techniques used in data analysis. It emphasizes practical applications and includes real-world examples to illustrate methods such as regression, classification, and resampling. Designed for readers with a background in statistics and some programming knowledge, it balances theoretical foundations with hands-on exercises, making it an essential resource for anyone looking to deepen their understanding of statistical modeling and machine learning.