This Movie Recommendation System leverages cosine similarity, a robust metric for measuring the similarity between movie features and user preferences. By analyzing user ratings and movie attributes such as genre, director, and actors, the system generates personalized recommendations tailored to individual tastes. Through the application of cosine similarity, this project enhances the movie-watching experience by suggesting relevant and enjoyable films, fostering user satisfaction and engagement.
source: https://www.kaggle.com/code/razamh/movie-recommendation-system-using-machine-learning