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Information Theory, Inference and Learning Algorithms
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 th...more
Hardcover, 640 pages
Published
September 25th 2003
by Cambridge University Press
(first published June 15th 2002)
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Hokey the Bayesian Bear says: "Only you can prevent the misguided use of p-values."
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I chose this to accompany my reading of Norvig's text on artificial intelligence. I thought the information theoretic concepts deepened my understanding of intelligent agents functioning in an information-deprived environment. The sections on genetic algorithms and neural networks gave a nifty information theoretic perspective on those topics, but I think other texts (such as Koza on genetic algorithms) were better reads.
I shall add this to my "reference" collection, for I ...more
I shall add this to my "reference" collection, for I ...more
I've been working through this chapter by chapter for about a month now. Loving it sofar!
Nick Black
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Recommended to Nick by:
Michael Mitzenmacher (Harvard CS)
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This book is amazing! Its a pretty esoteric approach to teaching machine learning and I don't think its a good introductory book on that subject. But for folks already versed in the topic, this book can shed a lot of new light and does a good job abstracting it with concepts from information theory and stats.
This book was my first in depth exposure to information theory and the proofs, often accompanied by helpful figures, were clear and, hell, even exciting. Its a much easier read ...more
This book was my first in depth exposure to information theory and the proofs, often accompanied by helpful figures, were clear and, hell, even exciting. Its a much easier read ...more
Excellent book about diverse topics in machine learning, statistics, information theory etc. Many exercises and applications.
Free to download on the internet!
Free to download on the internet!
A review of information theory, coding theory, and several machine learning and statistics topics, all from a Bayesian perspective. Low-density parity-check codes (which are used in HDTV) are very cool!
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