**Information Theory, Inference, and Learning Algorithms**

by David J. C. MacKay

**Publisher**: Cambridge University Press 2003**ISBN/ASIN**: 0521642981**ISBN-13**: 9780521642989**Number of pages**: 640

**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.

Download or read it online for free here:

**Download link**

(multiple formats)

## Similar books

**Algorithmic Information Theory**

by

**Peter D. Gruenwald, Paul M.B. Vitanyi**-

**CWI**

We introduce algorithmic information theory, also known as the theory of Kolmogorov complexity. We explain this quantitative approach to defining information and discuss the extent to which Kolmogorov's and Shannon's theory have a common purpose.

(

**6549**views)

**Generalized Information Measures and Their Applications**

by

**Inder Jeet Taneja**-

**Universidade Federal de Santa Catarina**

Contents: Shannon's Entropy; Information and Divergence Measures; Entropy-Type Measures; Generalized Information and Divergence Measures; M-Dimensional Divergence Measures and Their Generalizations; Unified (r,s)-Multivariate Entropies; etc.

(

**6536**views)

**Essential Coding Theory**

by

**Venkatesan Guruswami, Atri Rudra, Madhu Sudan**-

**University at Buffalo**

Error-correcting codes are clever ways of representing data so that one can recover the original information even if parts of it are corrupted. The basic idea is to introduce redundancy so that the original information can be recovered ...

(

**4173**views)

**Theory of Quantum Information**

by

**John Watrous**-

**University of Calgary**

The focus is on the mathematical theory of quantum information. We will begin with basic principles and methods for reasoning about quantum information, and then move on to a discussion of various results concerning quantum information.

(

**7231**views)