Advanced Analytics with Spark, 1st Edition eBook

Delivery: Can be download immediately after purchasing. For new customer, we need process for verification from 30 mins to 12 hours.
Version: PDF/EPUB. If you need EPUB and MOBI Version, please contact us.
Compatible Devices: Can be read on any devices.

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 setPredicting forest cover with decision treesAnomaly detection in network traffic with K-means clusteringUnderstanding Wikipedia with Latent Semantic AnalysisAnalyzing co-occurrence networks with GraphXGeospatial and temporal data analysis on the New York City Taxi Trips dataEstimating financial risk through Monte Carlo simulationAnalyzing genomics data and the BDG projectAnalyzing neuroimaging data with PySpark and Thunder

This is a digital product.

Advanced Analytics with Spark 1st Edition is written by Ryza, Sandy; Laserson, Uri; Owen, Sean; Wills, Josh and published by O’Reilly Media. The Digital and eTextbook ISBNs for Advanced Analytics with Spark are 9781491912768, 1491912766 and the print ISBNs are 9781491912768, 1491912766.