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

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. 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.

User’s Reviews

Editorial Reviews: Review “…a valuable reference…enjoyable and highly useful.” American Scientist”…an impressive book, intended as a class text on the subject of the title but having the character and robustness of a focused encyclopedia. The presentation is finely detailed, well documented, and stocked with artistic flourishes.” Mathematical Reviews”Essential reading for students of electrical engineering and computer science; also a great heads-up for mathematics students concerning the subtlety of many commonsense questions.” Choice”An utterly original book that shows the connections between such disparate fields as information theory and coding, inference, and statistical physics.” Dave Forney, Massachusetts 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.” Peter Dayan and Zoubin Ghahramani, Gatsby Computational Neuroscience Unit, University College, London”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”An excellent textbook in the areas of infomation theory, Bayesian inference and learning alorithms. Undergraduate and post-graduate students will find it extremely useful for gaining insight into these topics.” REDNOVA”Most of the theories are accompanied by motivations, and explanations with the corresponding examples…the book achieves its goal of being a good textbook on information theory.” ACM SIGACT News Book Description Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐Read the book is like talking to a teacher. I can feel the soul of the author. (He had passed away). The book contains solutions to selected problems that are convenient to me for self-study.

⭐Highly recommended. Very coherent and readable. Unique angle of view. The author didn’t try to scare the reader away like a lot of other authors did.

⭐If someone looking for a different perspective, interesting and challenging, this is a book to read.

⭐The hardcover is much better than the soft cover. Mackay was a visionary, can’t wait to read the book.

⭐This is a really good book. It serves as a good introduction to Information theory but it has enough depth and cover enough material be to interesting and insightful even to someone who has already studies the subject in depth. This book is fairly high level and though I found it very interesting and insightful it does not have enough practical information to be useful (on its own) for solving problems in information theory or writing learning algorithms.

⭐Other reviewers have provided all the details you need to know before buying.Just to chime in that this is one of the best technical books I have ever read.It brims with insight and beautiful illustrations of ideas both old and novel.Although you can find a free copy online, do consider getting the print version.It is a great tome to have, and Dr. MacKay certainly deserves the royalties.

⭐Good book on topic, well written.

⭐Coverage or detail? One may not be used to getting both. This book actually uses a detailed description of those questions “left for the reader” as a way to reinforce its pedagogy. I just love this book.

⭐A delightful tour of information theory and inference. I’m about half-way the book now, and every page has been a thrill.The author passed away too soon. But he leaves a lot behind in this book.

⭐A brilliant book written by someone who seems to have been a brilliant educator. I love the fact that you can read the whole book online before purchase – I found the online version excellent but wanted a hard copy… that is how useful this book is!

⭐An interesting read, well written and you can download the PDF for free but having the dead tree version as well to read in the bath is sooooo much better.

⭐A book that rewards effort. It combines many fascinating topics at the heart of modern technology, and does so with clarity and wit.

⭐This is unique among the books I have encountered on information theory at this level, indeed one of the most reader-friendly accounts of any mathematically complex topic that I have ever read. The style makes the (difficult) subject matter very accessible. There are plenty of illustrations, which really do help with understanding, as well as examples with (mostly) answers provided, which are also valuable. The provision of answers to examples is frowned upon by purists, who say readers should just work them out for themselves, but we can’t always succeed with every one, and I personally hate to be hung up on an example that I can’t do.To appreciate the benefits of Mackay’s approach, compare this book with the classic ‘Elements of Information Theory’ by Cover and Thomas. That book was first published in 1990, and the approach is far more ‘classical’ than Mackay. It is certainly less suitable for self-study than Mackay’s book. That said, I find Cover and Thomas very useful for providing the formal mathematical proofs of the theorems. After reading Mackay and understanding a topic, I then read Cover and Thomas on the same area and find the formal exposition of it, which complements Mackay nicely. I would not be without either book.PS: I have subsequently discovered an excellent series of lectures by the author available online, essentially covering the main topics of the book. The lectures clarify the rather dense presentation in the book, and I have found them invaluable. They can be found by Googling “Mackay information theory lectures”.

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