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Recommendation Systems
Movie Recommendation System

Movie Recommendation System

This project is a movie recommendation system built with Str

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What is Movie Recommendation System ?

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.

Features

  • Personalized Recommendations: Tailored suggestions based on user preferences and viewing history.
  • User Ratings Integration: Incorporates user ratings to refine recommendations.
  • Popular Movies Listing: Displays trending and highly-rated movies.
  • Genre-Based Filtering: Allows users to explore movies by specific genres.
  • Streaming Platform Integration: Provides information on where to watch recommended movies.
  • Interactive Interface: Easy-to-use interface with search and filter options.
  • Top 10 Recommendations: Generates a curated list of the top 10 picks for each selection.

How to use Movie Recommendation System ?

  1. Launch the Application: Open the Movie Recommendation System on your device.
  2. Select a Movie: Choose a movie you've watched or are interested in.
  3. View Recommendations: The system will display top 10 movie recommendations based on your selection.
  4. Filter Results: Use genre, rating, or streaming platform filters to narrow down suggestions.
  5. Provide Feedback: Rate movies to improve future recommendations.
  6. Explore More: Continue discovering new movies and expanding your watchlist.

Frequently Asked Questions

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.

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