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with Applications in R
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This book serves as a comprehensive guide to statistical learning, emphasizing practical applications and theoretical foundations. It covers essential topics such as regression, classification, and resampling methods, making complex concepts accessible to readers with a background in statistics and mathematics. The inclusion of real-world examples and case studies enhances understanding, while accompanying software tools facilitate hands-on learning. Ideal for students and professionals alike, it bridges the gap between statistical theory and practical implementation in data analysis.
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An Introduction to Statistical Learning, Gareth James, Robert Tibshirani, Trevor Hastie, Daniela Witten
- Language
- Released
- 2022
- Binding
- (Paperback)
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- Title
- An Introduction to Statistical Learning
- Subtitle
- with Applications in R
- Language
- English
- Publisher
- Springer US
- Released
- 2022
- Format
- Paperback
- Pages
- 624
- ISBN13
- 9781071614204
- Series
- Tags
- Science, Technology, Math Textbooks
- Rating
- 4.6 out of 5
- Description
- This book serves as a comprehensive guide to statistical learning, emphasizing practical applications and theoretical foundations. It covers essential topics such as regression, classification, and resampling methods, making complex concepts accessible to readers with a background in statistics and mathematics. The inclusion of real-world examples and case studies enhances understanding, while accompanying software tools facilitate hands-on learning. Ideal for students and professionals alike, it bridges the gap between statistical theory and practical implementation in data analysis.