Project 9 for the Data Science Bootcamp at SPICED Academy Berlin, by Lorena Ciutacu (https://github.com/lorenanda) and Daniela Morariu (https://github.com/DanielaMorariu1990).
The days of endless indecissive scrolling are over! We created a recommender system with a web interface that recommends you new movies based on your preferences. You only need to rate up to 15 movies and specify your preference for old vs. new movies, then you get a list of 5 movies along with their plot summary and trailer. We built this with:
- Python
- pandas, scikit-learn (NMF), surprise (SVD)
- HTML, CSS, Flask
- TMBD API
In a terminal:
- Clone this repo:
git clone https://github.com/lorenanda/movie-recommender.git - Install the necessary libraries:
pip install -r requirements.txt - Change the directory to the main application
cd flask_app - Get your API key from TMDB and write it in
config.py - Run these three commands:
export FLASK_APP=application.pyexport FLASK_DEBUG=1flask run
- Open the listed localhost http://127.0.0.1:5000/ in a browser.
- Grab some popcorn, lean back, and enjoy a recommended movie!
The project was tested on Chrome and Firefox!