Advanced Analytics with Spark: Patterns for Learning from Data at Scale
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2024-09-26
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2020-07-14
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Advanced Analytics with Spark: Patterns for Learning from Data at Scale

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

  • TitleAdvanced Analytics with Spark: Patterns for Learning from Data at Scale
  • BrandO'Reilly
  • ManufacturerO'Reilly Media
  • BindingPaperback
  • ProductGroupBook
  • ItemPartNumberblack & white illustrations
  • UnitCount1
  • EANs9781491912768