By Mahmoud Parsian
If you are prepared to dive into the MapReduce framework for processing huge datasets, this functional ebook takes you step-by-step in the course of the algorithms and instruments you must construct allotted MapReduce purposes with Apache Hadoop or Apache Spark. every one bankruptcy offers a recipe for fixing a big computational challenge, akin to construction a suggestion method. You’ll how one can enforce the perfect MapReduce answer with code so you might use on your projects.
Dr. Mahmoud Parsian covers uncomplicated layout styles, optimization suggestions, and information mining and desktop studying strategies for difficulties in bioinformatics, genomics, information, and social community research. This booklet additionally contains an outline of MapReduce, Hadoop, and Spark.
- Market basket research for a wide set of transactions
- Data mining algorithms (K-means, KNN, and Naive Bayes)
- Using large genomic info to series DNA and RNA
- Naive Bayes theorem and Markov chains for information and industry prediction
- Recommendation algorithms and pairwise rfile similarity
- Linear regression, Cox regression, and Pearson correlation
- Allelic frequency and mining DNA
- Social community research (recommendation structures, counting triangles, sentiment analysis)
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