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Bekkerman, Ron

Scaling up machine learning parallel and distributed approaches edited by Ron Bekkerman, Mikhail Bilenko, John Langford. - New York : Cambridge University Press, ©2012. - xvi, 475 p. ; 28 cm.

Includes bibliographical references and index.

License restrictions may limit access.

"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"--

9780521192248 = Scaling up machine learning

Machine learning.
Data mining.
Parallel algorithms.
Parallel programs (Computer programs)
COMPUTERS / Computer Vision & Pattern Recognition.

Q325.5 / .S28 2012

006.31 / BEK-S

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