Scaling up machine learning parallel and distributed approaches

By:

Bekkerman, Ron

Contributor(s):

Material type: Text

9780521192248

Subject(s):

DDC classification:

006.31 23 BEK-S

LOC classification:

Q325.5 .S28 2012

Other classification:

COM016000

Cambridge Books Online - Computer ScienceSummary: "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"--

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Books	IIITD Reference	Computer Science and Engineering	REF 006.31 BEK-S (Browse shelf(Opens below))	Available		003786

Total holds: 0

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Previous	REF 006.3 ZHO-D Data mining for co-location patterns :	REF 006.31 AFF-G Genetic algorithms and genetic programming :	REF 006.31 BAR-B Bayesian reasoning and machine learning	REF 006.31 BEK-S Scaling up machine learning	REF 006.31 BUD-F Fundamentals of deep learning :	REF 006.31 CHA-S Semi-supervised learning	REF 006.31 CHR-S An introduction to support vector machines :	Next

Includes bibliographical references and index.

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"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"--

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