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Pattern Recognition and Machine Learning

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ISBN-10: 0387310738

ISBN-13: 9780387310732

Edition: 2006

Authors: Christopher M. Bishop

List price: $99.99
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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 models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications. This…    
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Book details

List price: $99.99
Copyright year: 2006
Publisher: Springer New York
Publication date: 4/6/2011
Binding: Hardcover
Pages: 778
Size: 7.01" wide x 9.25" long x 0.67" tall
Weight: 4.202
Language: English

Probability distributions
Linear models for regression
Linear models for classification
Neural networks
Kernel methods
Sparse kernel machines
Graphical models
Mixture models and EM
Approximate inference
Sampling methods
Continuous latent variables
Sequential data
Combining models