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Learn the algorithms and tools you need to build MapReduce applications with Hadoop and Spark 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-stepthrough 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 * Apply t-test, joins, top-10, and correlation algorithms using MapReduce/Hadoop and Spark
* 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 * Apply t-test, joins, top-10, and correlation algorithms using MapReduce/Hadoop and Spark