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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

Implemented Using Machine Learning (K-Means Clustering Also) in Python

This repository contains a robust and user-friendly movie recommendation system built to enhance your movie-watching experience. Whether you're a film enthusiast or just looking for something new to watch, our system has you covered topics

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