Advanced Analytics with Spark: Patterns for Learning from Data at Scale by Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills (2nd Edition)
Requirements: ePUB Reader, 4.6MB
Overview: 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.
Genre: Non-Fiction, Computer Science, Programming
Download Instructions:
https://dailyuploads.net/hmz4t2i3frkl
(Closed Filehost) https://uploadrocket.net/cffw3gpyjehz/AAWS.rar.html
Requirements: ePUB Reader, 4.6MB
Overview: 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.
Genre: Non-Fiction, Computer Science, Programming
Download Instructions:
https://dailyuploads.net/hmz4t2i3frkl
(Closed Filehost) https://uploadrocket.net/cffw3gpyjehz/AAWS.rar.html
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