Pattern recognition and machine learning
"The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical mod...
Guardat en:
| Autor principal: | |
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| Format: | Livre papier |
| Idioma: | Anglais |
| Publicat: |
New York :
Springer
C 2006.
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| Col·lecció: | Information science and statistics
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| Matèries: | |
| Nota: |
Liste des errata disponible sur le site https://www.microsoft.com/en-us/research/wp-content/uploads/2016/05/prml-errata-1st-20110921.pdf Contient des exercices en fin de chapitres, et un choix de documents en appendice. |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Pattern recognition and machine learning, by Christopher M. Bishop, 1st ed. 2006, 2006, New York, Springer, Information Science and Statistics, 978-0-387-45528-0 |
Taula de continguts:
- 1. Introduction
- 2. Probability distributions
- 3. Linear models for regression
- 4. Linear models for classification
- 5. Neural networks
- 6. Kernel methods
- 7. Sparse Kernel machines
- 8. Graphical models
- 9. Mixture models and EM
- 10. Approximate inference
- 11. Sampling methods
- 12. Continuous latent variables
- 13. Sequential data
- 14. Combining models.