Information Theory, Inference and Learning Algorithms - Softcover

MacKay, David J. C.

 
9780521642989: Information Theory, Inference and Learning Algorithms

Synopsis

Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.

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From the Inside Flap

An instant classic, covering everything from Shannon's fundamental theorems to the postmodern theory of LDPC codes. You'll want two copies of this astonishing book, one for the office and one for the fireside at home. - Bob McEliece, California Institute of Technology

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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Other Popular Editions of the Same Title

9780521670517: Information Theory, Inference and Learning Algorithms (Student's International Edition)

Featured Edition

ISBN 10:  0521670519 ISBN 13:  9780521670517
Publisher: CAMBRIDGE UNIVERSITY PRESS, 2018
Softcover