[PDF.37pg] Scaling up Machine Learning: Parallel and Distributed Approaches
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Scaling up Machine Learning: Parallel and Distributed Approaches
From Cambridge University Press
[PDF.jo57] Scaling up Machine Learning: Parallel and Distributed Approaches
Scaling up Machine Learning: From Cambridge University Press epub Scaling up Machine Learning: From Cambridge University Press pdf download Scaling up Machine Learning: From Cambridge University Press pdf file Scaling up Machine Learning: From Cambridge University Press audiobook Scaling up Machine Learning: From Cambridge University Press book review Scaling up Machine Learning: From Cambridge University Press summary
| #156658 in Books | 2011-12-30 | Original language:English | PDF # 1 | 9.96 x1.06 x8.46l,2.20 | File type: PDF | 492 pages||0 of 0 people found the following review helpful.| Four Stars|By Kindle Customer|Nice coverage of a number of applications.|4 of 4 people found the following review helpful.| Dated collection of research material|By techuser|This book reads like a collection of dated papers (which are not even recent as of today).||"One of the landmark achievements of our time is the ability to extract value from large volumes of data. Engineering and algorithmic developments on this front have gelled substantially in recent years, and are quickly being reduced to practice in widely-avai
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 req...
You can specify the type of files you want, for your device.Scaling up Machine Learning: Parallel and Distributed Approaches | From Cambridge University Press. I was recommended this book by a dear friend of mine.
