Advanced analytics with Spark patterns from learning from data at scale
The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by presenting examples and a set of self-contained patterns for performing large-scale data analysis with Spark. You'll start with an introduction to Spark and its eco...
| Main Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Sebastopol, CA
O'Reilly Media
2017
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| Edition: | Second edition |
| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
| Summary: | The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by presenting examples and a set of self-contained patterns for performing large-scale data analysis with Spark. 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 |
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| Item Description: | Previous edition published: 2015. - Includes index |
| Physical Description: | 1 volume illustrations |
| ISBN: | 1491972947 9781491972946 1491972955 |