In this project, we implemented three models for a movie recommendation system: FunkSVD, Item-based Collaborative Filtering with Cosine Similarity, and Content-based Filtering with Ridge Regression. Using a range of machine learning and deep learning techniques, the project evaluates the effectiveness of each model to identify their strengths and weaknesses. The final goal is to determine the most suitable model to enhance the recommendation system and improve the user experience through an intuitive web interface.