Machine Learning - A Probabilistic Perspective (Hardcover, New)

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach. Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package-PMTK (probabilistic modeling toolkit)-that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

General

Imprint:	MIT Press
Country of origin:	United States
Series:	Adaptive Computation and Machine Learning series
Release date:	August 2012
First published:	2012
Authors:	Kevin P. Murphy
Dimensions:	235 x 206 x 43mm (L x W x T)
Format:	Hardcover
Pages:	1067
Edition:	New
ISBN-13:	978-0-262-01802-9
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	0-262-01802-0
Barcode:	9780262018029

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!