Machine learning: A recommender system in kdb+/q with MovieLens dataset

Nick Psaris, author of "Q-Tips, Fast, Scalable and Maintainable Kdb+," will use q to generate movie recommendations using a few different 'collaborative filtering' techniques on the MovieLens dataset: cosine similarity, singular value decomposition, and regularized gradient descent.

To make it more interesting, Nick will collect attendees favorite and least favorite movies so he can load their preferences for the demo. You can make your nominations here in the comment section, or send them to kxcommunity@kx.com .