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Advanced Analytics with Spark

By Sean Owen

Advanced Analytics with Spark Computer Science

Advanced Analytics with Spark

Only 3 items left in stock
Description
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 * Analyzing neuroimaging data with PySpark and Thunder
Product details
Binding:
Paperback
Edition:
1
Number of Pages:
260
Release Date:
2015-04-30
Publication Date:
2016-04-30
Publisher:
O'Reilly UK Ltd.
Languages:
Original: English
ISBN10:
1491912766
ISBN13:
9781491912768
Weight:
488 g
Height:
179 cm
Width:
233 cm
Thickness:
20 cm

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Very good
Almost no signs of wear. Book pages have no markings, accessories are intact and all other media are in good condition.
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