کتاب Pattern Recognition and Machine Learning

کتاب Pattern Recognition and Machine Learning

کتاب Pattern Recognition and Machine Learning اثر Christopher M. Bishop زبان اصلی

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.

About the author

Christopher Michael Bishop (born 7 April 1959) FREng, FRSE, is the Laboratory Director at Microsoft Research Cambridge and professor of Computer Science at the University of Edinburgh and a Fellow of Darwin College, Cambridge. Chris obtained a Bachelor of Arts degree in Physics from St Catherine’s College, Oxford, and a PhD in Theoretical Physics from the University of Edinburgh, with a thesis on quantum field theory.

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