Advanced Analytics with Spark: Patterns for Learning from Data at Scale (Paperback)

Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills

Advanced Analytics with Spark: Patterns for Learning from Data at Scale (Paperback)

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商品描述

Apache Spark is emerging as one of the most popular technologies for performing analytics on huge datasets, and this practical guide shows you how to harness Spark’s power for approaching a variety of analytics problems. You’ll learn how to apply common techniques, such as classification, clustering, collaborative filtering, anomaly detection, dimensionality reduction, and Monte Carlo simulation to fields such as genomics, security, and finance.

Advanced Analytics with Spark supplies complete implementations that analyze large public datasets, and acts as an introduction to using these techniques and other best practices in Spark programming.

  • Become familiar with the Spark programming model and ecosystem
  • Learn general approaches in data science
  • Discover which machine learning tools make sense for particular problems
  • Acquire code from GitHub that can be adapted to many uses

This book will interest both data science professionals and aspiring data scientists, students studying learning techniques for analyzing large datasets, and scientists interested in using Spark as a research tool.

商品描述(中文翻譯)

Apache Spark正成為在大數據分析領域中最受歡迎的技術之一，這本實用指南將向您展示如何利用Spark的強大功能解決各種分析問題。您將學習如何應用常見的技術，例如分類、聚類、協同過濾、異常檢測、降維和蒙特卡羅模擬，應用於基因組學、安全和金融等領域。

《Advanced Analytics with Spark》提供了分析大型公共數據集的完整實現，並介紹了在Spark編程中使用這些技術和其他最佳實踐的方法。

本書將使數據科學專業人士和有志於成為數據科學家的人感興趣，同時也適合學習分析大型數據集的學生以及希望將Spark作為研究工具的科學家。

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