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Ted Dunning @ eHarmony (for real)

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


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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  • Jon M.

    Thanks everyone for coming, you can find a video of the talk at https://vimeo.com/eharmony/review/95539804/370f93dbae

    1 · May 19, 2014

  • Andrew G.

    https://github.com/tdunning/ponies
    Example ponies project.

    1 · May 13, 2014

    • David M.

      Ted said at the meetup that the github repository was still "work in progress". It looks like you get music data from the public-domain source at musicbrainz.org, and treat the machine-generated log in the github data file as "user listening behavior" against that music file. Pig scripts are used to process the data prior to analyzing it with Mahout.

      May 14, 2014

    • David M.

      I expect more code will be added to the repository in the days to come. If you didn't get a hard copy of the book, I think you can download it at http://www.mapr.com/p...­. In it, he discusses this recommender system.

      May 14, 2014

  • Bill V.

    Enjoyed this and learned a lot.

    May 14, 2014

  • Jeff W.

    Smart, funny, informative, talked about very high level concepts in accessible terms. Much thanks.

    1 · May 13, 2014

  • Jeff W.

    Great talk. Much of it way over my head. But what was under my head, was also reallly informative, funny and interesting. And then Ted actually gave me the hat off of his head (seriously). A cool red MapR hat, yeah!

    1 · May 13, 2014

  • Stefano

    Anybody freeing up their spot hopefully not at the last minute so wait listed can better plan?

    May 13, 2014

  • Brian L.

    Opening my spot up now. Too much to do to work remotely all day. Hope to see you guys next time.

    May 12, 2014

  • Scott E.

    Will this be recorded?

    May 10, 2014

    • Lisa C.

      Yes, it will be recorded and put on Vimeo. Please give it a few days before checking for it.

      2 · May 12, 2014

  • Dan B.

    If any of you ever visit NorCal, I invite you to my ML class. Project 1, predict the stock market. Until then you can join remotely: http://spy611.com/blog/class

    2 · May 4, 2014

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