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: Advanced Analytics with Spark: Patterns for Learning from Data at Scale, 2nd Edition
: Sandy Ryza, Uri Laserson, Sean Owen, Josh Wills
: O'Reilly Media
: 2017
: 271
: True PDF, EPUB, AZW3
: 10 Mb
: English

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 datasets 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.

Youll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniquesincluding classification, clustering, collaborative filtering, and anomaly detectionto 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, youll find the books 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 datasets
Discover which machine learning tools make sense for particular problems
Acquire code that can be adapted to many uses









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