For undergraduate research, me and a friend made a recommendation engine web service (very similar to Directed Edge) using Python + Tornado. I've put it on the

For undergraduate research, me and a friend made a recommendation engine web service (very similar to Directed Edge) using Python + Tornado. I've put it on the back burner because other priorities necessitate my attention for now. But I certainly wouldn't mind help. I've implemented a recommendation algorithm using a modified version of TANGET, but it is untested. I'd love it if someone with more knowledge in ML than I stepped in and worked on it. I wouldn't even mind if they completely scrapped my algorithm and made a new one. I think this would be a good opportunity for anyone interested in ML because everything except the recommendation algorithm is decently solidified: it includes several tools for testing, and it exposes everything through a simple REST API. Theoretically, it would just be a matter of dropping in your algorithm and seeing how it goes. Practically, however, I must warn that code comments are ridiculously sparse and there isn't a single unit test, because I'm a terrible person. There is, however, a decent integration test suite and some solid documentation. It is available here: http://github.com/heliumpigs/snowball http://github.com/heliumpigs/snowball These are also several related open source projects that we made and our project depends on: * A tool for running blackbox tests on REST APIs: http://github.com/heliumpigs/catnap http://github.com/heliumpigs/catnap * A key-value store built on top of MySQL (inspired by FriendFeed's use case): http://github.com/ysimonson/scarecrow http://github.com/ysimonson/scarecrow * Some useful stuff for Tornado: http://github.com/ysimonson/oz http://github.com/ysimonson/oz Email me if you're interested (info in profile). PS: I'm posting here in case anyone else is interested.