A Python-based movie recommender system that provides personalized suggestions using two approaches:
- Content-based algorithm: recommends movies similar to a selected title by analyzing their attributes.
- User-based collaborative filtering: recommends movies based on a user’s preferences and ratings, leveraging patterns from similar users.
-
Built on large datasets containing a wide variety of movies and series.
-
Allows users to type a movie title and get recommendations for the most similar movies (Content-based).
-
Provides personalized recommendations based on user ratings and preferences, which can be modified as needed (Collaborative filtering).
-
Offers a function that automatically generates the top 15 movies of all time.
-
Delivers accurate and relevant recommendations to satisfy user needs.