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Information Theory, Inference and Learning Algorithms

David J. C. MacKay




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 | #118923 in Books |  Cambridge University Press |  2003-10-06 | Original language:English | PDF # 1 |  9.69 x1.34 x7.44l,3.25 | File type: PDF | 640 pages

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||2 of 5 people found the following review helpful.| It is fun to read this book|By M. ZENG|First of all, the shipping is fast and the price is low. It is a new book but the price is lower than the used one. Second, the book itself is worth reading for fun. It combines so many interesting topics in an unified framework: Bayesian framework, from information theory to neuro network.|75 of 77 people found the following review helpf| |"...a valuable reference...enjoyable and highly useful." |American Scientist

"...an impressive book, intended as a class text on the subject of the title but having the character and robustness of a focused encyclopedia. The presentation is finely

Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication ...

You can specify the type of files you want, for your gadget.Information Theory, Inference and Learning Algorithms   |  David J. C. MacKay. I really enjoyed this book and have already told so many people about it!

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