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Advanced Analytics with Spark: Patterns for Learning from Data at Scale - Softcover

Ryza, Sandy; Laserson, Uri; Owen, Sean

 
9781491972953: Advanced Analytics with Spark: Patterns for Learning from Data at Scale

Inhaltsangabe

In the second edition of 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. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming.

You’ll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques—including classification, clustering, collaborative filtering, and anomaly detection—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 the book’s patterns useful for working on your own data applications.

With this book, you will:

  • Familiarize yourself with the Spark programming model
  • Become comfortable within the Spark ecosystem
  • Learn general approaches in data science
  • Examine complete implementations that analyze large public data sets
  • Discover which machine learning tools make sense for particular problems
  • Acquire code that can be adapted to many uses

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Über die Autorin bzw. den Autor

Sandy Ryza develops algorithms for public transit at Remix. Prior, he was a senior data scientist at Cloudera and Clover Health. He is an Apache Spark committer, Apache Hadoop PMC member, and founder of the Time Series for Spark project. He holds the Brown University computer science department's 2012 Twining award for "Most Chill".

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9789352135714: Advanced Analytics with Spark: Patterns for Learning from Data at Scale

Vorgestellte Ausgabe

ISBN 10:  9352135717 ISBN 13:  9789352135714
Verlag: Shroff/O'Reilly, 2017
Softcover