Unsupervised learning
Subtitle: foundations of neural computation
By: edited by Geoffrey Hinton and Terrence J. Sejnowski.
Contributors: Hinton, Geoffrey E.; Sejnowski, Terrence J.
Series: Computational neuroscience
Publisher: MIT Press; A Bradford Book
Published: 1999
Place of publication: Cambridge, Mass
Language: eng
Number of pages: 398
Subjects: Learning -- Physiological aspects.; Neural networks (Computer science); Learning -- Computer simulation.; Neural computers.
Description: This volume, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans.

They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.
Notes: Includes bibliographical references and index.
"A Bradford book."