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Personalized Movie Recommender System
This project implements an Item-Based Collaborative Filtering (IBCF) recommendation system that analyzes user movie ratings to generate personalized top-3 movie suggestions. The model identifies similar movies based on rating patterns and recommends unwatched films that align with each user's preferences.