Explore live open-source projects and AI models.

This project offers a content-based movie recommendation system, designed to transcend generic suggestions and curate personalized movie lists just for you.

A cross domain recommendation system that utilizes movie lens data set.

A movie recommendation system built using Scala, Spark and Hadoop

A Django-based movie recommender that uses a trained ML model with a Jupyter notebook for customization. Features an interactive web UI with auto-suggestions and supports both local setup and cloud deployment.

Develop a site that analyzes user preferences and recommends movies based on their taste

🎬 Create an ML-powered movie recommendation system that uses content-based filtering to deliver 30 clever, funny, and tailored film picks based on your favorite movie. Harness Python, pandas, and scikit-learn—with a sprinkle of humor—to spark epic movie nights and uncover hidden cinematic treasur... Read more

A movie recommendation system trained on the MovieLens 20 Million dataset. This system makes use of Collaborative filtering methods to come up with recommendations for a particular user.

MoRe is a movie recommendation system built using cosine similarity algorithm. It is a content based filtering recommendation system i.e. it uses past activity data of the users and based on that it recommends the movies to the users.

Survey of collaborative filtering techniques and their effectiveness as a movie recommendation system

Recommendation system for movies using the MovieLens dataset