Description
Book Synopsis: 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.
Details
Looking to expand your knowledge in information theory, inference, and learning algorithms? Look no further! Our groundbreaking book, "Information Theory, Inference and Learning Algorithms," is a must-have for anyone interested in contemporary science and engineering.
With over 400 exercises and rich illustrations, this textbook will take you on an exciting journey through the heart of communication, signal processing, data mining, and more. Gain practical skills that you can apply to real-world scenarios, such as data compression and error-correction techniques.
What sets this textbook apart is its seamless integration of theory and applications. You'll not only learn the fundamental concepts of information theory but also understand how they are applied in various fields like computational neuroscience, bioinformatics, and cryptography. You'll also discover cutting-edge topics like convolutional codes, neural networks, and digital fountain codes.
Not only is this book highly informative, but it's also highly enjoyable. Along the way, you'll come across intriguing interludes on crosswords, evolution, and sex - perfect for keeping you engaged and entertained.
Whether you're a self-learner or looking for a textbook for your undergraduate or graduate course, "Information Theory, Inference and Learning Algorithms," is your ultimate resource. Professionals in computational biology, financial engineering, and machine learning will also find this book to be an unparalleled entry point into these subjects.
Don't miss out on this opportunity to expand your knowledge and enhance your skills. Get your hands on our book today and unlock a world of possibilities! Click here to order now.
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