Description: Pattern Recognition And Machine Learning, Hardcover by Bishop, Christopher M., ISBN 0387310738, ISBN-13 9780387310732, Used Good Condition, Free shipping in the US This is the first textbook on pattern recognition to present the Bayesian viewpoint. Th 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 th includes a self-contained introduction to basic probability theory.
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Book Title: Pattern Recognition And Machine Learning
Number of Pages: Xx, 778 Pages
Publication Name: Pattern Recognition and Machine Learning
Language: English
Publisher: Springer New York
Item Height: 0.7 in
Subject: Probability & Statistics / General, Intelligence (Ai) & Semantics, Cognitive Psychology & Cognition, Computer Vision & Pattern Recognition
Publication Year: 2006
Type: Textbook
Item Weight: 75.7 Oz
Subject Area: Mathematics, Computers, Psychology
Author: Christopher M. Bishop
Item Length: 9.3 in
Series: Information Science and Statistics Ser.
Item Width: 7 in
Format: Hardcover
