Description:
Paperback / softback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too large or the speed and throughput requirements are too demanding. Researchers and practitioners
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Scaling Up Machine Learning: Parallel and Distributed Approaches Paperback - 2018
by Ron Bekkerman (Editor); Mikhail Bilenko (Editor); John Langford (Editor)
Details
- Title Scaling Up Machine Learning: Parallel and Distributed Approaches
- Author Ron Bekkerman (Editor); Mikhail Bilenko (Editor); John Langford (Editor)
- Binding Paperback
- Pages 491
- Volumes 1
- Language ENG
- Publisher Cambridge University Press
- Date 2018-03-29
- ISBN 9781108461740 / 1108461743
- Weight 1.86 lbs (0.84 kg)
- Dimensions 10 x 7 x 0.99 in (25.40 x 17.78 x 2.51 cm)
-
Themes
- Aspects (Academic): Science/Technology Aspects
- Dewey Decimal Code 006.31
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Scaling up Machine Learning
by Ron Bekkerman
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Scaling up Machine Learning: Parallel and Distributed Approaches
by Ron Bekkerman
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Paperback / softback. New. In many practical situations it is impossible to run existing machine learning methods on a single computer, because either the data is too large or the speed and throughput requirements are too demanding. Researchers and practitioners will find here a variety of machine learning methods developed specifically for parallel or distributed systems, covering algorithms, platforms and applications.
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Scaling up Machine Learning: Parallel and Distributed Approaches
by Edited by Ron Bekkerman , Mikhail Bilenko , John Langford
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Cambridge University Press, 2018. Paperback. New. 1st reprint edition. 492 pages. 9.88x7.01x1.50 inches.
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Scaling up Machine Learning
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SCALING UP MACHINE LEARNING : PARALLEL & DISTRIBUTED APPROACHES 2018
by BEKKERMAN
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