Alfred Street (University of Auckland Store)
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Pattern Recognition And Machine Learning
Hardback Edition: 1
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply
graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.
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Pages : 740
Publisher : Springer Verlag
Publication date : 2011
Subjects: Non-fiction, Science And Technology, Social Sciences, Computing And IT, Psychology, Computer Vision, Mathematical Theory Of Computation, Cognition & Cognitive Psychology