Two years ago, I conducted a fascinating research project at Spotify as part of my Master’s Thesis. I learned several useful ML techniques, which I believe any Data Scientist should have in their toolkit. And today, I’m here to walk you through one of them.
During that time, I spent 6 months trying to build a prediction model and then deciphering its inner workings. My goal was to understand what made users satisfied with their music experience.
It wasn’t so much about predicting whether a user was happy (or not), but rather understanding the underlying factors that contributed to their happiness (or lack thereof).