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Scaling up machine learning

Ron Bekkerman · 2011

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About the book

"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"--

Book details

Year
2011
Language
English
Publisher
Cambridge University Press
Editions
1
Pages
475
ISBN
9780521192248

Data source: Wikidata

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