Machine-Learning with Renthop

Contributed by David Letzler, Kyle Gallatin and Christopher Capozzola They enrolled in the NYC Data Science Academy 12-week full time Data Science Bootcamp program taking place between January 9th, 2017 and March 31st, 2017. The original article can be found here. For this project, we took on the Two Sigma Connect: Rental Listing Inquiries Challenge on Kaggle. The rental website Renthop provided us with a csv of data from 120,000 listings and asked us to produce a model to predict whether a given listing would receive "low," "medium," or "high" interest. The model would be judged by predicting a test set, with the log-loss formula determining its effectiveness.