##Description: This is a very simple web app built in Flask, which uses the MoveLens dataset of 100k user ratings of popular movies in order to make recommendations on what movies a given user may want to watch. It was a quick(ish) weekend experiment to make a web-driven interface to explore pure Python objects, with no database on the backend. As a result, it will take a couple minutes to load the first time, in order to build the network of recommendations.
##Requirements:
- Python 3 (3.4 recommended)
- MovieLens
100k dataset (
ml-100k.zip
), unzipped into./datasets/ml-100k
- Flask
- Install via
pip3 install -r requirements.txt
- Install via
##Instructions:
- Download/clone all files from this repo to your machine
- Download and unzip the required dataset, described above
- Run on the command line: "python3 ui.py"*
- Open http://127.0.0.1:5000/ in a web browser window
- Explore the site to find ratings for movies, movie rankings, and recommendations for each user based on their previous ratings
######* Note: This application is under development, and uses debug mode and as such, should not be used in a production environment!
####Acknowledgements: The MovieLens data sets used for this project were collected by the [GroupLens Research Project] (http://grouplens.org) at the University of Minnesota.
This work is neither endorsed nor sponsored by the University of Minnesota nor the GroupLens Research Group.
This project and the provided data are for non-commercial research purposes.