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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.
"About this title" may belong to another edition of this title.
- PublisherCambridge University Press
- Publication date2003
- ISBN 10 0521642981
- ISBN 13 9780521642989
- BindingPaperback
- LanguageEnglish
- Number of pages642
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Information Theory, Inference and Learning Algorithms
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Cambridge University Press, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
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Condition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present. Seller Inventory # M00521642981-G
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Information Theory, Inference and Learning Algorithms
Published by
Cambridge University Press, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
Used
Softcover
Seller: medimops, Berlin, Germany
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Condition: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages. Seller Inventory # M00521642981-V
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INFORMATION THEORY INFERENCE & LEARNING
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ISBN 13: 9780521642989
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Information Theory, Inference and Learning Algorithms
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ISBN 10: 0521642981
ISBN 13: 9780521642989
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Information Theory, Inference and Learning Algorithms
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ISBN 13: 9780521642989
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Information Theory, Inference and Learning Algorithms
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ISBN 13: 9780521642989
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Information Theory, Inference and Learning Algorithms (Hardcover)
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ISBN 10: 0521642981
ISBN 13: 9780521642989
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Hardcover. Condition: new. Hardcover. 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. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning. 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. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes — the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521642989
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Information Theory, Inference
Published by
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ISBN 10: 0521642981
ISBN 13: 9780521642989
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Information Theory, Inference and Learning Algorithms
Published by
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ISBN 10: 0521642981
ISBN 13: 9780521642989
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Information Theory, Inference and Learning Algorithms
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Hardcover. Condition: Brand New. 640 pages. 10.00x1.75x1.25 inches. In Stock. This item is printed on demand. Seller Inventory # __0521642981
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