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Paramètres
- 607pages
- 22 heures de lecture
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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.
Achat du livre
An Introduction to Statistical Learning, Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
- Langue
- Année de publication
- 2021
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- (rigide)
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- Sous-titre
- with Applications in R
- Langue
- Anglais
- Éditeur
- Springer-Verlag GmbH
- Publié
- 2021
- Format
- rigide
- Pages
- 607
- ISBN13
- 9781071614174
- Séries
- Mots clés
- Nonfiction, Manuels, Technologie & Ingénierie, Informatique & Internet, Science, Technologie, Manuels de mathématiques
- Évaluation
- 4,6 sur 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.