In this project, we utilize the Youtube API to access Youtube Shorts data
to study which content, creator, timing, and engagement factors are associated with viral videos, and whether Machine Learning can predict which Shorts will become unusually popular. A high level roadmap of our project includes parsing the shorts data, performing EDA on the dataset, and then testing various models like classification and logistic regression with the goal of finding which identifies popular short form the video accurately.