Data Algorithms
Recipes for Scaling up with Hadoop and Spark
Publisher: O'Reilly Media
Final Release Date: August 2014
Pages: 500

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Learn the algorithms and tools you need to build MapReduce applications with Hadoop for processing gigabyte, terabyte, or petabyte-sized datasets on clusters of commodity hardware. With this practical book, Author Mahmoud Parsian, head of the big data team at Illumina, takes you step-by-step through the design of machine-learning algorithms, such as Naive Bayes and Markov Chain, and shows you how apply them to clinical and biological datasets, using MapReduce design patterns.

  • Apply MapReduce algorithms to clinical and biological data, such as DNA-Seq and RNA-Seq
  • Use the most relevant regression/analytical algorithms used for different biological data types
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February 2015 (est.)