Information Theory, Inference, and Learning Algorithms

information theory

Information Theory, Inference, and Learning Algorithms
by David J. C. MacKay

eBook Details :

Hardcover: 640  pages
Publisher:Cambridge University Press 2003
Language: English
ISBN :13: 9780521642989

eBook Description:
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 systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks.

 Download or read it online here: Information Theory, Inference, and Learning Algorithms

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