Advanced Analytics with Spark: Patterns for Learning from Data at Scale, Second Edition
Sandy Ryza, Uri Laserson, Sean Owen, Josh WillsHow much do you like this book?
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n 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.
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.
Categories:
Year:
2017
Edition:
2
Publisher:
O’Reilly Media
Language:
english
Pages:
275
ISBN 10:
1491972955
ISBN 13:
9781491972953
File:
PDF, 5.21 MB
Your tags:
IPFS:
CID , CID Blake2b
english, 2017
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