How to Build a Play Recommendation Engine for the Avignon Festival with Dataiku DSS

Hi everyone, my name is Clara and I joined Dataiku's data science team a while ago for an internship. Today I'm going to tell you about a project that was inspired by an overheard conversation during lunch: Alivia Smith (who you are already familiar with if you are an avid reader of our blog) was struggling with the schedule of the Avignon Festival, a French theater festival; struggling because there are so many plays and events happening, but no real guide or documentation to help her decide on her schedule. Since we're a great big loving family at Dataiku, and we're always enthusiastic about playing with data, a couple of us data scientists figured we could use machine learning to build a play recommender for her, so she could have insights regarding which plays she might like, based on her tastes and the theater community's appreciation. We computed several recommendations for Alivia using a method known as collaborative filtering. Essentially, she gave us several plays she had already seen and liked, and from those we deduced a list of other plays she may like, with a score (i.e., an estimation of how much she would like them).