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The application uses content based filtering to make recommendations. For every movie selected, 12 recommendations are made based on their cosine similarity with the selected movie. An API feteches the poster image of the movie and displays them in an image grid to the user The database offers nearly 5000 movies to select from

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gmayuri1904/Movie-Recommendation-System

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Movie-Recommendation-System

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https://gmayuri1904-movie-recommendation-system-app-qnkabd.streamlit.app/

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The application uses content based filtering to make recommendations.
For every movie selected, 12 recommendations ar e made based on their cosine similarity with the selected movie.
The database offers nearly 5000 movies to select from.
Backend is developed entirely with python and front end using Streamlit.
This application is deployed on Heroku

About

The application uses content based filtering to make recommendations. For every movie selected, 12 recommendations are made based on their cosine similarity with the selected movie. An API feteches the poster image of the movie and displays them in an image grid to the user The database offers nearly 5000 movies to select from

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