Publication Date: October 1, 2007 ISBN-10: 0387310738 ISBN-13 :978-0,387,310,732 | Version: Version 1. In 2006. Cole. 2011 2nd printing
This is the first textbook of pattern recognition, Bayesian view. This book presents approximate inference algorithms allow fast approximate answers in the case of the exact answer is not feasible. It uses a graphical model to describe the probability distribution, in the absence of other books graphical models, machine learning. No previous knowledge of pattern recognition and machine learning concepts is assumed. Familiar with the basic requirements of multivariate calculus and linear algebra, and probability will be useful, but not necessary, because this book include a separate introduction to basic probability theory and some experience.