Advanced Analytics with Spark: Patterns for Learning from Data at Scale / Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills


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

Now you can buy Books online in USA,UK, India and more than 100 countries.
*Terms and Conditions apply
Disclaimer: All product data on this page belongs to buy amazon.
No guarantees are made as to accuracy of prices and information.

Contact Us

Create a Bookshelf of your Favorite books
Get it on Google Play        Get it on Google Play
For Any Queries please don't hesitate to contact us at
USA +1(760)3380762
+1(650) 9808080
India +91 9023011224
India +91 9023011224 (Whatsapp)
Donate
Buy Books online because as an Amazon Associate we earn from qualifying purchases.