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Pattern Recognition and Machine Learning (Information Science and Statistics)

Christopher M. Bishop




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 | #13287 in Books |  imusti |  2007-10-01 | Original language:English | PDF # 1 |  9.25 x7.25 x1.75l,3.90 | File type: PDF | 738 pages

 | Springer

||15 of 16 people found the following review helpful.| Still (one of) the best|By e|I recently had to quickly understand some facts about the probabilistic interpretation of pca. Naturally I picked up this book and it didn't disappoint. Bishop is absolutely clear, and an excellent writer as well.

In my opinion, despite the recent publication of Kevin Murphy's very comprehensive ML book, Bishop is still a better read. T| ||From the reviews: |"This beautifully produced book is intended for advanced undergraduates, PhD students, and researchers and practitioners, primarily in the machine learning or allied areas...A strong feature is the use of geometric illustration and intuitio

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 calc...

You easily download any file type for your device.Pattern Recognition and Machine Learning (Information Science and Statistics)   |  Christopher M. Bishop. A good, fresh read, highly recommended.

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