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Movie recommendation system based on hybrid recommender and clustering

Movie recommendation system based on movielens dataset. Bayesian approach used to predict likely rating of the movie

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A content-based movie recommendation system that suggests similar movies based on your preferences, built with Python and Streamlit.

🚀 End to End Movie Recommendation system built with NextJS, Flask, MySQL, TailwindCSS and AWS 🛸. Performs 📝 Content based, Collaborative and Neural Collaborative recommendations. --> Ongoing project

Combines user-based and item-based recommendation systems to deliver personalized movie suggestions, utilizing user preferences and film characteristics.

A self-hosted movie recommendation system based on your favorites movies on Jellyfin. Host it yourself, by following the instructions in the README. Or checkout a hosted instance here: https://jrh1823rhui34y8.gzuo.me/login

With the rapid adoption of smartphones, tablets, and mobile apps, they are increasingly becoming part of children’s daily life for amusement and education. According to MarketingProfs, 75% of American children under 8 have access to a smartphone or tablet [1]. According to a survey conducted by P... Read more

Built a Movie Recommendation System which will take as input a movie title from the user and return the top 50 recommended movies to the user based on the input movie.

In this repository, we have built a recommendation engine for movies from scratch using basic numpy and pythonic operations. Also, at the end of the project, we have tried to implement matrix factorization algorithm to predict implicit ratings and then recommend movies to the users