The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
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Select a product to estimate shipping.“The Elements of Statistical Learning” is a comprehensive textbook offering a rigorous introduction to the field of statistical learning. This second edition builds upon the original’s foundational concepts, providing a detailed exploration of data mining, inference, and prediction techniques.
Key Highlights
- Gain a solid understanding of core statistical learning methods.
- Explore a wide range of algorithms for data analysis and modeling.
- Benefit from clear explanations and numerous examples illustrating practical applications.
- Suitable for readers with a background in mathematics and statistics.
Useful Facts
- Publisher: Springer
- Publication Date: February 9, 2009
- Edition: Second Edition 2009
- Language: English
- Pages: 767
- Dimensions: 9.3 x 6 x 1.4 inches
Good Fit For
- Students and researchers in computer science, statistics, and related fields.
- Data scientists and analysts seeking to deepen their knowledge of statistical modeling.
- Anyone interested in learning the theoretical foundations of machine learning.
| Main Specification | |
|---|---|
| Marque | by Trevor Hastie (Author) or Robert Tibshirani (Author) or Jerome Friedman (Author) & 0 more Format: Hardcover |
| Date de publication | 2009 or February 9 |
| Poids de l'article | 3,1 livres |
| Product information | |
| Langue | changements climatiques |
| Others | |
| Type de produit | Intelligence & Semantics |
| Édition | Second Edition 2009 |
| Éditeur | Springer |
| Longueur d'impression | 767 pages |
| L'objectif de l'initiative est de mettre en place un système d'échange d'informations entre les États membres. | 0387848576 |
| ISBN 13 | 978-0387848570 |
| Dimensions | 9.3 x 6 x 1.4 inches |
| ISBN 10 | 0387848576 |
| ISBN 13 | 978-0387848570 |