Recommender system for movies

Repository to demonstrate how to use machine learning to generate recommendations. It's use movie lens data. This dataset (ml-latest-small) describes 5-star rating and free-text tagging activity from MovieLens, a movie recommendation service. It contains 100004 ratings and 1296 tag applications across 9125 movies.

It's uses Surprise "a Python scikit building and analyzing recommender systems".

Requirements

1. Python
2. Anaconda

Project setup

1. Clone this repository and enter the repository directory
2. Create your enviroment using: conda env create -f environment.yml
3. Activate your enviroment:

   Windows

   activate movie-ratings

   Linux or OSX

   source activate movie-ratings
4. Run Jupyter notebook jupyter notebook

See Movie-Recommendations notebook for more details