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Advanced analytics with Spark :patterns for learning from data at scale /Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills.
Beijing : O'Reilly, 2017
xii, 264 pages :illustrations ;24 cm
Ký hiệu phân loại (DDC): 006.312
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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