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Pattern Recognition and Machine Learning

Af: Christopher M. Bishop Engelsk Paperback

Pattern Recognition and Machine Learning

Af: Christopher M. Bishop Engelsk Paperback
Tjek vores konkurrenters priser

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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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.

Produktdetaljer
Sprog: Engelsk
Sider: 778
ISBN-13: 9781493938438
Indbinding: Paperback
Udgave:
ISBN-10: 1493938436
Udg. Dato: 23 aug 2016
Længde: 44mm
Bredde: 254mm
Højde: 180mm
Forlag: Springer-Verlag New York Inc.
Oplagsdato: 23 aug 2016
Forfatter(e): Christopher M. Bishop
Forfatter(e) Christopher M. Bishop


Kategori Mønstergenkendelse


ISBN-13 9781493938438


Sprog Engelsk


Indbinding Paperback


Sider 778


Udgave


Længde 44mm


Bredde 254mm


Højde 180mm


Udg. Dato 23 aug 2016


Oplagsdato 23 aug 2016


Forlag Springer-Verlag New York Inc.

Kategori sammenhænge