Lauren Oldja, MSPH - Supervised Learning at the Movies

For those following along here or on my Twitter account it's no secret that I am currently enrolled at Metis in their 12-week data science bootcamp, which marries the structure of daily morning problem solving with highly self-guided and project-based afternoons/evenings/weekends. The expectations are high, and the deadlines are "intentionally unfair", giving the three months a hackathon-lite vibe. Some projects featured on this blog, this post included, accompany projects completed and presented for Metis. For this project I scraped Box Office Mojo in order to build a predictive linear regression model. At first blush, predicting domestic box office gross is hardly worthy of machine learning: instinctively we know it must be a function of increasing marketing and production budgets.