Pattern Recognition and Machine Learning (Information Science and Statistics)
| Autor | Christopher M. Bishop |
| 6981481311 | |
| Idioma | Germany - English |
| Terminal correspondiente | Android|iPhone|iPad|PC |
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Machine Learning 1. Introduction Part I. Foundations: 2. A gentle start 3. A formal learning model 4. Learning via uniform convergence 5. The bias-complexity trade-off 6. The VC-dimension 7. Non-uniform learnability 8. The runtime of learning Part II. From Theory to Algorithms: 9. Linear predictors 10. Boosting 11. Model selection and validation 12. Convex learning problems 13. Regularization ...
Introduction to Machine Learning with Python: A Guide for Data Scientists. Sarah Guido, O'Reilly UK Ltd, 2016 Pattern Recognition and Machine Learning (Information Science and Statistics). Christopher M. Bishop, 2007 Understanding Machine Learning: From Theory to Algorithms. Shai Shalev-Shwartz und Shai Ben-David, Cambridge University Press, 2014
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Find many great new & used options and get the best deals for Springer Proceedings in Mathematics and Statistics: Mathematical Methodologies in Pattern Recognition and Machine Learning : Contributions from the International Conference on Pattern Recognition Applications and Methods 2012 30 (2012, Hardcover) at the best online prices at eBay!
Pattern Recognition and Machine Learning provides excellent intuitive descriptions and appropriate-level technical details on modern pattern recognition and machine learning. It can be used to teach a course or for self-study, as well as for a reference. … I strongly recommend it for the intended audience and note that Neal (2007) also has given this text a strong review to complement its ...
The Nature of Statistical Learning Theory (Information Science and Statistics) | Vladimir N. Vapnik | ISBN: 9781441931603 | Kostenloser Versand für alle Bücher mit Versand und Verkauf duch Amazon.
Christopher M. Bishop: Pattern Recognition and Machine Learning. Information Science and Statistics. Springer-Verlag, Berlin 2008, ISBN 978-0-387-31073-2. David J. C. MacKay: Information Theory, Inference and Learning Algorithms. Cambridge University Press, Cambridge 2003, ISBN 978-0-521-64298-9 .
Bishop, C. M. (2008) Pattern Recognition and Machine Learning. Information Science and Statistics. Springer, Berlin 2008 Information Science and Statistics. Springer, Berlin 2008 Google Scholar
Bishop, Pattern Recognition and Machine Learning. Information Science and Statistics. Springer, Berlin (2008) Information Science and Statistics. Springer, Berlin (2008) Google Scholar
This is a very readable book by an authority on this subject. The book starts with the statistical learning theory, pioneered by the author and co-worker's work, and gradually leads to the path of discovery of support vector machines.
Christopher M. Bishop: Pattern Recognition and Machine Learning. Information Science and Statistics, Springer-Verlag, 2008, ISBN 978-0387310732 Nello Cristianini, John Shawe-Taylor: Kernel Methods for Pattern Classification .
