2006, ISBN: 9780387310732

[ED: Gebunden], [PU: Springer US], The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the un… Mehr…

[ED: Gebunden], [PU: Springer US], 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 completely new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern..., DE, [SC: 0.00], Neuware, gewerbliches Angebot, 778, [GW: 1482g], 2006. Corr. 2nd Printing 2011 edition, Banküberweisung, PayPal, [CT: Sonstiges / Sonstiges]<

2006, ISBN: 9780387310732

[ED: Gebunden], [PU: Springer US], The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the un… Mehr…

[ED: Gebunden], [PU: Springer US], 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 completely new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern..., DE, [SC: 0.00], Neuware, gewerbliches Angebot, 778, [GW: 1482g], 2006. Corr. 2nd Printing 2011 edition, PayPal, [CT: Sonstiges / Sonstiges]<

ISBN: 9780387310732

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 … Mehr…

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. New Textbooks>Hardcover>Technology>Xxxsoftware Engr>* Desc Unknown, Springer New York Core >2 >T<

ISBN: 9780387310732

Find Pattern Recognition and Machine Learning by Christopher M. Bishop in Hardcover and other formats in Computers > Computer Vision & Pattern Recognition. Computers 9780387310732, Springer