Movie Recommendation System

I built this project because I was tired of scrolling through Netflix for 30 minutes just to rewatch The Office. Recommendation systems are everywhere - Netflix, Spotify, Amazon - and I wanted to understand how they actually work under the hood. This system uses collaborative filtering to find patterns in how people rate movies. The basic idea is that if you and someone else liked the same movies in the past, you'll probably like similar movies in the future. I implemented both user-based and item-based approaches and compared their performance. It was a great way to learn about recommendation algorithms and matrix factorization techniques. Plus, I actually use it now to find movies to watch.