using tmdb datasets from kaggle
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Book Recommendation System
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The Movie Recommender System is an AI-powered recommendation engine designed to help users discover movies they will love. It leverages data from the TMDB dataset available on Kaggle to provide personalized suggestions based on user preferences. The system analyzes various factors, including genres, ratings, and popularity, to deliver tailored movie recommendations.
• Personalized Recommendations: Get movie suggestions based on your preferences and viewing history.
• Multiple Filters: Narrow down recommendations by genre, year, ratings, and popularity.
• User Ratings Integration: See how other users have rated movies to make informed choices.
• Trending Movies: Stay updated with the latest and trending films in the industry.
• Family-Friendly Options: Filter out content that may not be suitable for all age groups.
1. How does the Movie Recommender System ensure privacy?
The system uses anonymized data and does not store personal information, ensuring your privacy is protected.
2. Can I save my favorite movie recommendations?
Yes, you can bookmark or save movies you’re interested in watching for later.
3. Does the system include newly released movies?
Yes, the system is regularly updated with the latest movies from the TMDB dataset, ensuring you get the most recent recommendations.