
Categories  Download eBook: Information Theory, Inference and Learning Algorithms  
Book Catagory:Data Structures and Algorithms
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. financial engineering, and machine learning. This textbook introduces Information theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparsegraph codes for errorcorrection. A toolbox of inference techniques, including messagepassing 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 errorcorrecting codes, including lowdensity paritycheck codes, turbo codes, and digital fountain codes  the twentyfirst 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 selflearning 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.
More Data Structures and Algorithms eBooks: Linear Programming: Foundations and Extensions Algorithms and Data Structures With Applications to Graphics and Geometry Matters Computational: Ideas, Algorithms, Source Code Exploring Randomness Ant Colony Optimization  Techniques and Applications Fundamental Data Structures Introduction to Design Analysis of Algorithms Solving NPComplete Problems Think Complexity: Complexity Science and Computational Modeling Traveling Salesman Problem, Theory and Applications Knapsack Problems: Algorithms and Computer Implementations RealWorld Applications of Genetic Algorithms New Frontiers in Graph Theory Search Algorithms for Engineering Optimization Data Structures Succinctly, Part 2 
