Collaborative filtering in shallow waters (ONSITE)

In this meetup I am going to introduce collaborative filtering basics. I will show you how to code in python a simple recommendation system. We will use the http://www.grouplens.org/node/73 dataset to do some movie recommendations.

 

All you need is python installed on your machine. We will use numpy and scipy. That's all!!!

 

When you feel comfortable with it we will see how we can scale it with hadoop by using a super easy web-service called http://mortardata.com/

 

WEBEX LINK: https://meetings.webex.com/collabs/#/meetings/detail?uuid=M8US8Z6IGXSOIO8SLFQNXAK5NZ-61RD

Meeting Number:[masked]

Host Key :704916

A link to the files we need

http://www.meetup.com/Learning-Machine-Learning-by-Example/files/

 

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  • Noir

    I've written my own 3-dimensional collaborative filtering algorithm using Pearson correlations to recommend items to users. I was pleasantly surprised with the material Nik presented at the meetup. Even though Nik contended we were floating in "shallow waters" aka doing simple stuff, we touched on some "deep water" issues, such as the mechanics behind low rank factorization and singular value deposition. He even provided a Python script to everyone that executed recommendations using SVD. That was pretty nifty. I highly recommend this meeting. Two thumbs up.

    January 25, 2013

    • Noir

      sorry for the typos ;)

      January 25, 2013

  • Monosij D.

    Really great in going through examples and learning about the fundamental algorithms behind CF and how the logic applies. Nick went into some of the details of SVD. And how it is done at a large scale such as Amazon.

    January 23, 2013

  • Brian H.

    Nikolaos does a great job at presenting and preparing topics and materials so the students can practice their technique.

    January 23, 2013

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Rafaël

We just grab a coffee and speak French. Some people have been coming every week for months... it creates a kind of warmth to the group.

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