This project implements a collaborative filtering-based movie recommendation system using the MovieLens dataset and the Surprise library in Python.
This recommendation system uses collaborative filtering to predict movie ratings and suggest movies to users.
It is built using:
- Python
- Surprise Library (for collaborative filtering)
- MovieLens Dataset (for training and testing)
The system is implemented in Google Colab and can be easily adapted for other datasets.
The dataset used is the MovieLens Small Dataset, which contains:
- 100,000 ratings from 600 users on 9,000 movies.
- Movies file (
movies.csv): Contains movie titles and genres. - Ratings file (
ratings.csv): Contains user IDs, movie IDs, and ratings.
📥 Download Dataset → MovieLens
To run this project, install the required libraries:
pip install pandas numpy scikit-surprise matplotlib seaborn