Movie Recommendation System using Collaborative Filtering

This project creates a movie recommendation system using collaborative filtering techniques. The system suggests movies to users based on the ratings provided by other similar users. Using data such as movie ratings and user preferences, the system calculates similarity scores between users or movies to generate recommendations. The system can be optimized by using matrix factorization or user-item interaction matrices.