Title Pattern recognition and machine learning / Christopher M. Bishop

Published New York : Springer, ©2006

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Description 1 online resource (xx, 738 pages) : illustrations (chiefly color) Series Information science and statistics Information science and statistics. Contents 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 Notes Textbook for graduates Bibliography Includes bibliographical references (pages 711-728) and index Notes Print version record Subject Pattern perception. Pattern recognition systems. Machine learning. Pattern recognition systems -- Textbooks Machine learning -- Textbooks Pattern recognition systems -- Problems, exercises, etc Machine learning -- Problems, exercises, etc Mathematical statistics. Pattern Recognition, Automated Machine Learning Mathematical statistics Machine learning Pattern perception Pattern recognition systems Patroonherkenning. Machine-learning. Redes neurais. Reconhecimento de padrões. Aprendizado computacional. Genre/Form Electronic books exercise books. Textbooks Problems and exercises Problems and exercises. Problèmes et exercices. Form Electronic book LC no. 2006922522 ISBN 9780387455280 0387455280

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