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Author Ryza, Sandy, author.

Title Advanced analytics with Spark / Sandy Ryza, Uri Laserson, Sean Owen and Josh Wills.

Edition First edition.
Publication Info. Beijing ; Sebastopol, CA : O'Reilly, 2015.
Location Call No. Status
 Nichols Adult Nonfiction  006.312 SPA    AVAILABLE
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Description xii, 260 pages : illustrations ; 23 cm
Note Includes index.
Summary "In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. You'll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques-classification, collaborative filtering, and anomaly detection among others-to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you'll find these patterns useful for working on your own data applications. Patterns include: Recommending music and the Audioscrobbler data set, Predicting forest cover with decision trees, Anomaly detection in network traffic with K-means clustering, Understanding Wikipedia with Latent Semantic Analysis, Analyzing co-occurrence networks with GraphX, Geospatial and temporal data analysis on the New York City Taxi Trips data, Estimating financial risk through Monte Carlo simulation, Analyzing genomics data and the BDG project and Analyzing neuroimaging data with PySpark and Thunder." from publisher's website.
Subject Spark (Electronic resource : Apache Software Foundation)
Big data.
Data mining -- Computer programs.
Added Author Laserson, Uri, author.
Owen, Sean, author.
Wills, Josh, author.
Note Subtitle on cover: Patterns for learning from data at scale
ISBN 9781491912768
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