9781108461740-1108461743-Scaling up Machine Learning (Parallel and Distributed Approaches)

Scaling up Machine Learning (Parallel and Distributed Approaches)

ISBN-13: 9781108461740
ISBN-10: 1108461743
Edition: 1
Author: Bekkerman, Ron
Publication date: 2018
Publisher: Cambridge University Press
Format: Paperback 492 pages
FREE shipping on ALL orders

Book details

ISBN-13: 9781108461740
ISBN-10: 1108461743
Edition: 1
Author: Bekkerman, Ron
Publication date: 2018
Publisher: Cambridge University Press
Format: Paperback 492 pages

Summary

Acknowledged authors Bekkerman, Ron wrote Scaling up Machine Learning (Parallel and Distributed Approaches) comprising 492 pages back in 2018. Textbook and eTextbook are published under ISBN 1108461743 and 9781108461740. Since then Scaling up Machine Learning (Parallel and Distributed Approaches) textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

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. Solutions presented in the book cover a range of parallelization platforms from FPGAs and GPUs to multi-core systems and commodity clusters, concurrent programming frameworks including CUDA, MPI, MapReduce, and DryadLINQ, and learning settings (supervised, unsupervised, semi-supervised, and online learning). Extensive coverage of parallelization of boosted trees, SVMs, spectral clustering, belief propagation and other popular learning algorithms and deep dives into several applications make the book equally useful for researchers, students, and practitioners.





Rate this book Rate this book

We would LOVE it if you could help us and other readers by reviewing the book