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From Hackathon to production: building a large scale recommendation engine

• epylinkn 15y ago
  excited!
• dekayed 15y ago
  Could you recommend some good resources for learning more about collaborative filtering? I'd love to help hack, but feel like I should learn more first.
  • derwiki 15y ago
    Most of what I learned was from Programming Collective Intelligence (http://amzn.com/0596529325 http://amzn.com/0596529325). If you're in the Bay Area, Noisebridge has a self-taught machine learning class that I went to for a while (great group, I just couldn't make the time commitment).
    • seymourz 15y ago
      for most of the fundamentals on Collaborative Filtering, You may check Chapters 8 and 9 from the following online book. https://docs.google.com/viewer?url=http%3A%2F%2Finfolab.stanford.edu%2F~ullman%2Fmmds%2Fbook.pdf https://docs.google.com/viewer?url=http%3A%2F%2Finfolab.stan...
• tl10 15y ago
  have you looked at Mahout? https://cwiki.apache.org/confluence/display/MAHOUT/Itembased+Collaborative+Filtering https://cwiki.apache.org/confluence/display/MAHOUT/Itembased...
  • derwiki 15y ago
    Hm, I haven't. This suggests that Mahout might not work well for datasets on the scale we're dealing with (working toward 1 billion membership rows): http://lucene.472066.n3.nabble.com/Mahout-not-giving-recommendations-with-large-data-sets-td641249.html http://lucene.472066.n3.nabble.com/Mahout-not-giving-recomme... But that's also an older article, and things might be better. Mahout might be worth checking out.