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Robin Anil

Robin Anil
Software Engineer, Google

Website | @robinanil

Robin is a Committer at the Apache Software Foundation where he works with the Mahout Machine Learning community. He is also a co-author of “Mahout in Action” by Manning Publications, a book on how Mahout is used to perform Machine learning on Terabytes of data with ease.

He used to be a Tech Lead on the ML infrastructure for Minekey Inc, a valley based startup which focussing on recommendations and behavioral targeting for publisher content. He was introduced to the newly born Mahout community through the Google Summer of Code program while he was a dual-degree student at IIT Kharagpur. Since then, he has been trying to model machine learning algorithms in to the Map/Reduce format and have successfully merged his Complementary Naive Bayes and Frequent Pattern Mining implementations with the Mahout code base. He is currently working as a Software Engineer at Google, Bangalore. He finds time from work to contribute actively to the Mahout community.

Sessions

Data: Analytics and Visualization
Location: Oregon Ballroom 203
Robin Anil (Google), Ted Dunning (MapR Technologies)
Average rating: **...
(2.75, 4 ratings)
This hands-on tutorial aims at learning the basics of the important machine learning algorithms in Mahout. It aims to help you get it up and running on a Hadoop cluster. Mahout is open source implementation of a collection of algorithms designed from ground up to sift through terabytes of data and help bring out important patterns which are otherwise not in the reach of standard tools. Read more.