Pattern Recognition and Machine Learning Christopher M. Bishop

By:

Bishop, Christopher M

Material type: Text

TextLanguage: English Publication details: Springer 2006 New YorkEdition: 1st EdDescription: 738p. 17.78 x 3.84 x 25.4 cmISBN:

9781493938438

Subject(s):

DDC classification:

006.42 BIS

Summary: 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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Holdings
Item type	Current library	Call number	Status	Barcode
Books	Rashtriya Raksha University	006.4 BIS (Browse shelf(Opens below))	Available	11508
Books	Rashtriya Raksha University	6.42 BIS (Browse shelf(Opens below))	Available	8122
Books	Rashtriya Raksha University	6.42 BIS (Browse shelf(Opens below))	Available	8123

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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