Items related to Information Theory, Inference and Learning Algorithms
Synopsis
Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.
"synopsis" may belong to another edition of this title.
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.
-
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.
Other Popular Editions of the Same Title
Search results for Information Theory, Inference and Learning Algorithms
Stock Image
Information Theory, Inference and Learning Algorithms
Published by
Cambridge University Press (edition Illustrated), 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
Used
Paperback
Seller: BooksRun, Philadelphia, PA, U.S.A.
Seller rating 5 out of 5 stars
Paperback. Condition: Very Good. Illustrated. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported. Seller Inventory # 0521642981-8-1
Quantity: 1 available
Stock Image
Information Theory, Inference and Learning Algorithms
Published by
Cambridge University Press, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
Used
Hardcover
Seller: Books From California, Simi Valley, CA, U.S.A.
Seller rating 5 out of 5 stars
Hardcover. Condition: Very Good. Seller Inventory # mon0003752942
Quantity: 5 available
Seller Image
Information Theory, Inference and Learning Algorithms
Published by
Cambridge University Press, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
Used
Softcover
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers. Seller Inventory # 1752094-5
Quantity: 3 available
Stock Image
Information Theory, Inference and Learning Algorithms
Published by
Cambridge University Press, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
Used
Softcover
Seller: More Than Words, Waltham, MA, U.S.A.
Seller rating 5 out of 5 stars
Condition: Good. . . All orders guaranteed and ship within 24 hours. Before placing your order for please contact us for confirmation on the book's binding. Check out our other listings to add to your order for discounted shipping. Seller Inventory # WAL-B-6a-001894
Quantity: 1 available
Stock Image
INFORMATION THEORY INFERENCE & LEARNING
Published by
Cambridge University Press, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
New
Softcover
Seller: Speedyhen, London, United Kingdom
Seller rating 5 out of 5 stars
Condition: NEW. Seller Inventory # NW9780521642989
Quantity: 1 available
Seller Image
Information Theory, Inference, and Learning Algorithms
Published by
Cambridge University Press, 2019
ISBN 10: 0521642981
ISBN 13: 9780521642989
Used
Softcover. 4to
Seller: Chamblin Bookmine, Jacksonville, FL, U.S.A.
Seller rating 5 out of 5 stars
Softcover. 4to. Condition: Very Good. 22nd printing. Glossy light blue covers are clean with straight edges and pointed corners. Spine is uncreased with a lightly bumped head. Text block is square. Binding is tight. 628p. Interior is unmarked with crisp white pages through out. Seller Inventory # 110548
Quantity: 1 available
Seller Image
Information Theory, Inference and Learning Algorithms
Published by
Cambridge University Press, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
Used
Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers. Seller Inventory # 1752094-5
Quantity: 3 available
Seller Image
Information Theory, Inference and Learning Algorithms
Published by
Cambridge University Press, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
New
Softcover
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 1752094-n
Quantity: Over 20 available
Stock Image
Information Theory, Inference and Learning Algorithms
Published by
Cambridge University Press, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
New
Softcover
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In. Seller Inventory # ria9780521642989_new
Quantity: Over 20 available
Seller Image
Information Theory, Inference and Learning Algorithms (Hardcover)
Published by
Cambridge University Press, Cambridge, 2003
ISBN 10: 0521642981
ISBN 13: 9780521642989
New
Hardcover
Seller: CitiRetail, Stevenage, United Kingdom
Seller rating 5 out of 5 stars
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
Quantity: 1 available