Information Theory, Inference and Learning Algorithms
David J. C. MacKay
Sold by Kennys Bookstore, Olney, MD, U.S.A.
AbeBooks Seller since 9 October 2009
New - Hardcover
Condition: New
Quantity: 1 available
Add to basketSold by Kennys Bookstore, Olney, MD, U.S.A.
AbeBooks Seller since 9 October 2009
Condition: New
Quantity: 1 available
Add to basket2003. Sixth Printing 2007. Hardcover. Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering. Num Pages: 640 pages, 1 colour illus. 40 tables 390 exercises. BIC Classification: PH; TJ; UM; UY. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 251 x 192 x 35. Weight in Grams: 1500. 640 pages, 1 colour illus. 40 tables 390 exercises. Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering. Cateogry: (P) Professional & Vocational; (U) Tertiary Education (US: College). BIC Classification: PH; TJ; UM; UY. Dimension: 251 x 192 x 35. Weight: 1494. . . . . . Books ship from the US and Ireland.
Seller Inventory # V9780521642989
This is an extraordinary and important book, generous with insight and rich with detail in statistics, information theory, and probabilistic modeling across a wide swathe of standard, creatively original, and delightfully quirky topics. David MacKay is an uncompromisingly lucid thinker, from whom students, faculty and practitioners all can learn.
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Zoubin Ghahramani and Peter Dayan
Gatsby Computational Neuroscience Unit, University College London.
An utterly original book that shows the connections between such disparate fields as information theory and coding, inference, and statistical physics.
Dave Forney, M.I.T.
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