This project is a movie recommendation system built with Str
contoh model klasifikasi
Movie Match
Find and discover movies based on your preferences
Get personalized recommendations based on your preferences
recommendations
Find Hugging Face models by task
recommending movies based on content-based
online museum with facial emotion and adaptive music
Find crop recommendations based on inputs
Danmarks planter - hvem mangler?
Find recommended movies by title, cast, crew, or genre
Get a personalized recommendation using AI
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.