This article introduces Mahout, a library for scalable machine learning, and studies potential applications through two Mahout projects. It was written by Linda Terlouw. Linda is a computer scientist who works on Data Science (Data Analysis, Data Visualization, Process Mining).
Apache Mahout is a library for scalable machine learning. Originally a subproject of Apache Lucene (a high-performance text search engine library), Mahout has progressed to be a top-level Apache project.
While Mahout has only been around for a few years, it has established itself as a frontrunner in the field of machine learning technologies. Mahout has currently been adopted by: Foursquare, which uses Mahout with Apache Hadoop and Apache Hiveto power its recommendation engine; Twitter, which creates user interest models using Mahout; and Yahoo!, which uses Mahout in their anti-spam analytic platform. Other commercial and academic uses of Mahout have been catalogued at https://mahout.apache.org/general/powered-by-mahout.html.
This Refcard will present the basics of Mahout by studying two possible applications:
In this article there are 10 sections:
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