Scaling up machine learning
Subtitle: parallel and distributed approaches
By: [edited by] Ron Bekkerman, Mikhail Bilenko, John Langford
Publisher: Cambridge University Press
Published: 2011
Place of publication: Cambridge; New York
Language: eng
Number of pages: 475
ISBN-13: 9780521192248
Subjects: COMPUTERS / Computer Vision & Pattern Recognition; Parallel algorithms; Machine learning; Parallel programs (Computer programs); Data mining
Description: "This book presents an integrated collection of representative approaches for scaling up machine learning and data mining methods on parallel and distributed computing platforms. Demand for parallelizing learning algorithms is highly task-specific: in some settings it is driven by the enormous dataset sizes, in others by model complexity or by real-time performance requirements. Making task-appropriate algorithm and platform choices for large-scale machine learning requires understanding the benefits, trade-offs, and constraints of the available options"--
Notes: Includes index.