Collaborative Filtering Movie Recommendation with Matrix Factorization

This project builds a movie recommendation system using collaborative filtering with matrix factorization techniques like Singular Value Decomposition (SVD). Matrix factorization decomposes the user-item matrix into lower-dimensional matrices, which can be used to make predictions and recommend movies. The project includes building a recommendation engine using data such as user ratings and movie information.