Le livre est actuellement en rupture de stock
Paramètres
- 624pages
- 22 heures de lecture
En savoir plus sur le livre
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.
Achat du livre
An Introduction to Statistical Learning, Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani
- Langue
- Année de publication
- 2022
- product-detail.submit-box.info.binding
- (souple)
Nous vous informerons par e-mail dès que nous l’aurons retrouvé.
Modes de paiement
Il manque plus que ton avis ici.
- Sous-titre
- with Applications in R
- Langue
- Anglais
- Éditeur
- Springer US
- Publié
- 2022
- Format
- souple
- Pages
- 624
- ISBN13
- 9781071614204
- Séries
- Mots clés
- Nonfiction, Manuels, Technologie & Ingénierie, Informatique & Internet, Science, Technologie, Manuels de mathématiques
- Évaluation
- 4,6 sur 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.