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Pattern recognition and machine learning

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 othe...

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Detalles Bibliográficos
Autor principal: Bishop, Christopher M
Lenguaje:eng
Publicado: Springer 2006
Materias:
Acceso en línea:http://cds.cern.ch/record/998831
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author Bishop, Christopher M
author_facet Bishop, Christopher M
author_sort Bishop, Christopher M
collection CERN
description 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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spelling cern-9988312021-04-22T02:05:12Zhttp://cds.cern.ch/record/998831engBishop, Christopher MPattern recognition and machine learningComputing and ComputersThis 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.Springeroai:cds.cern.ch:9988312006
spellingShingle Computing and Computers
Bishop, Christopher M
Pattern recognition and machine learning
title Pattern recognition and machine learning
title_full Pattern recognition and machine learning
title_fullStr Pattern recognition and machine learning
title_full_unstemmed Pattern recognition and machine learning
title_short Pattern recognition and machine learning
title_sort pattern recognition and machine learning
topic Computing and Computers
url http://cds.cern.ch/record/998831
work_keys_str_mv AT bishopchristopherm patternrecognitionandmachinelearning