Movie recommended system

A movie recommendation system uses algorithms to suggest films based on user preferences, past behavior, and similar users' tastes. It often employs collaborative filtering, which analyzes patterns in user interactions (e.g., ratings, views), and content-based filtering, which matches movie attributes (genre, actors, directors) to the user's tastes. Hybrid methods combine both techniques for better accuracy. Machine learning models, like neural networks, further refine predictions by learning from vast amounts of data. Personalized recommendations aim to improve user experience by presenting relevant movies, boosting engagement, and potentially increasing user retention on platforms like Netflix or Amazon Prime.

Built With

• python
• sql