This document describes a project to predict the number of seasons for a TV show using information scraped from IMDB. It involved scraping data on over 20,000 TV shows, cleaning the data, exploring relationships between features, and building a ridge regression model to predict seasons based on ratings, popularity, runtime and other factors. The model performed reasonably with a testing score of 0.270, and future work could involve incorporating additional data like actor/director rankings and budgets to improve predictions.