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E-book

Title Scaling up machine learning : parallel and distributed approaches / edited by Ron Bekkerman, Mikhail Bilenko, John Langford
Published New York : Cambridge University Press, [2012]
©2012

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Description 1 online resource (xvi, 475 pages) : illustrations
Contents Cover; Scaling Up Machine Learning; Title; Copyright; Contents; Contributors; Preface; CHAPTER 1 Scaling Up Machine Learning: Introduction; 1.1 Machine Learning Basics; 1.2 Reasons for Scaling Up Machine Learning; 1.2.1 Large Number of Data Instances; 1.2.2 High Input Dimensionality; 1.2.3 Model and Algorithm Complexity; 1.2.4 Inference Time Constraints; 1.2.5 Prediction Cascades; 1.2.6 Model Selection and Parameter Sweeps; 1.3 Key Concepts in Parallel and Distributed Computing; 1.3.1 Data Parallelism; 1.3.2 Task Parallelism; 1.4 Platform Choices and Trade-Offs; 1.5 Thinking about Performance
Summary This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies
Bibliography Includes bibliographical references and index
Notes Print version record
Subject Machine learning.
Data mining.
Parallel algorithms.
Parallel programs (Computer programs)
Data Mining
Machine Learning
Data mining
Machine learning
Parallel algorithms
Parallel programs (Computer programs)
Form Electronic book
Author Bekkerman, Ron, editor.
Bilenko, Mikhail, 1978- editor.
Langford, John, 1975- editor.
LC no. 2011016323
ISBN 9781139042918
1139042912
9781139216937
1139216937