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Ted Dunning @ eHarmony (for real)

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Ted Dunning @ eHarmony (for real)

Details

12:00 arrival and lunch served
12:30 talk starts
13:30 end of Q&A

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Title: Machine learning with Apache Mahout

Abstract

Machine learning at large scale is challenging, and the open source Apache Mahout project is a good way to tackle it. Plus, Mahout just got a lot better with release of the new 0.8 version on July 25, 2013. There are improvements throughout Mahout, but particularly strong additions in clustering and recommendation algorithms and in the excellent Mahout math library. Mahout is slimmer, faster and more effective.

Mahout committer Ted Dunning (MapR) will talk about these updates to the opensource Apache Mahout project and then show how you can build a simple but powerful recommender using co-occurrence to determine preferences. It’s easier than you think, particularly with some tips and tricks that will be discussed. One of the best short cuts to practical and effective recommendation is to use search technology such as Solr for deploying the Mahout recommendation engine – find out more at the meet-up. Bio

Ted Dunning is Chief Application Architect for MapR Technologies. Ted has held Chief Scientist positions at Veoh Networks, ID Analytics and at MusicMatch, (now Yahoo Music). Ted is responsible for building the most advanced identity theft detection system on the planet, as well as one of the largest peer-assisted video distribution systems and ground-breaking music and video recommendations systems. Ted has 15 issued and 15 pending patents. Opinionated about software and data mining and passionate about open source, he is an active participant of Hadoop and its community and loves helping projects get going with new technologies. Ted is project Champion for Apache Drill and is also a PMC member and commiter for Apache Zookeeper and Apache Mahout projects. Ted also bought the drinks at one of the very first Hadoop User Group meetings.

Ted earned a BS degree in electrical engineering from the University of Colorado; a MS degree in computer science from New Mexico State University; and a Ph.D. in computing science from Sheffield University in the United Kingdom. Please bring your tickets for validation.

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