This project is a movie recommendation system built with Str
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recommending movies based on content-based
A movie recommendation system is a tool designed to suggest movies based on user preferences, viewing history, and ratings. Built with Streamlit, this system leverages advanced algorithms to analyze data and provide personalized recommendations. Its primary goal is to help users discover new movies they are likely to enjoy, enhancing their entertainment experience.
What algorithms does the system use?
The system employs collaborative filtering and content-based filtering to provide accurate recommendations.
Can I save my favorite recommendations?
Yes, you can bookmark or save movies for later viewing directly from the recommendations.
How often are the recommendations updated?
Recommendations are updated regularly based on new releases, user ratings, and trending movies.