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Scaling up Machine Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

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Bekkerman, Ron; Bilenko, Mikhail; Langford, John 作者

Cambridge University Press

译者

2011-12-30 出版日期

492 页数

USD 90.00 价格

Hardcover

丛书系列

9780521192248 图书编码

Scaling up Machine Learning 在线电子书图书标签: 机器学习数据挖掘分布式并行计算机 MachineLearning 计算机科学集体智慧

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Scaling up Machine Learning 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2024

Scaling up Machine Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2024

Scaling up Machine Learning 在线电子书用户评价

评分☆☆☆☆☆

不是我要的distributed learning.

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虽然一开始说是面向工程师的，但还是有点过于偏向理论了，而且是由一篇篇独立论文组成的，深浅不一，内容感觉太杂，什么领域的都有

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asdasda

评分☆☆☆☆☆

虽然一开始说是面向工程师的，但还是有点过于偏向理论了，而且是由一篇篇独立论文组成的，深浅不一，内容感觉太杂，什么领域的都有

评分☆☆☆☆☆

asdasda

Scaling up Machine Learning 在线电子书著者简介

Scaling up Machine Learning 在线电子书图书目录

Scaling up Machine Learning 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Scaling up Machine Learning 在线电子书图书描述

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.

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