Pattern Recognition and Machine Learning (Information Science and Statistics)
Get and download textbook Pattern Recognition and Machine Learning (Information Science and Statistics) for free
Categories: Pattern Recognition, Machine learning. Contributors: Christopher M. Bishop - Author. Format: Hardcover
Pattern Recognition and Machine Learning new edition
Download free books for 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 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
This volume features key contributions from the International Conference on Pattern Recognition Applications and Methods, (ICPRAM 2012,) held in Vilamoura, Algarve, Portugal from February 6th-8th, 2012. The conference provided a major point of collaboration between researchers, engineers and practitioners in the areas of Pattern Recognition, both from theoretical and applied perspectives, with a focus on mathematical methodologies. Contributions describe applications of pattern recognition techniques to real-world problems, interdisciplinary research, and experimental and theoretical studies w
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
author christopher m bishop format hardback language english publication year 17 08 2006 series information science and statistics subject computing it subject 2 computing professional programming title pattern recognition and machine learning information science and statistics author christopher m bishop publisher springer verlag publication date aug 17 2006 pages 738 binding hardcover edition 1 st dimensions 7 25 wx 9 25 hx 1 75 d isbn 0387310738 subject computers artificial intelligence des
Pattern Recognition and Machine Learning Textbook
