Making investment decisions in the film industry is a wonderfully hard problem. The signals received during a film pitch are simply not enough to determine whether or not you're betting on a flop. This project explores designing a model that predicts the gross domestic of a film to help investors decide whether or not to invest in a film.

• Built a Polynomial Linear Regression model using sklearn, and fit with engineered features.
• Scraped data from BoxOfficeMojo using Scrapy and BeautifulSoup