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Data Analytics with Hadoop: An Introduction for Data Scientists

Amazon.com Price:  $16.89 (as of 18/04/2019 22:25 PST- Details)

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Description

Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. As an alternative of deployment, operations, or software development on a regular basis associated with distributed computing, you’ll focus on particular analyses you’ll be able to build, the data warehousing techniques that Hadoop provides, and higher order data workflows this framework can produce.

Data scientists and analysts will discover ways to perform quite a lot of techniques, from writing MapReduce and Spark applications with Python to the usage of advanced modeling and data management with Spark MLlib, Hive, and HBase. You’ll also learn about the analytical processes and data systems to be had to build and empower data products that can deal with—and in fact require—huge amounts of data.

  • Understand core concepts at the back of Hadoop and cluster computing
  • Use design patterns and parallel analytical algorithms to create distributed data analysis jobs
  • Learn about data management, mining, and warehousing in a distributed context the usage of Apache Hive and HBase
  • Use Sqoop and Apache Flume to ingest data from relational databases
  • Program complex Hadoop and Spark applications with Apache Pig and Spark DataFrames
  • Perform machine learning techniques such as classification, clustering, and collaborative filtering with Spark’s MLlib

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