Week 10 Project:

Movie Recommender System

This project was completed in week 10 of the Data Science Bootcamp at Spiced Academy in Berlin, together with Pietro Passarella.

We built a movie recommender with a web interface utilizing the small movielens dataset, which includes a collection of 9742 movies previously rated by 610 users.

The aim of the project was to explore and utilize the surprise library. The current version is not exactly the most efficient and practical application since it takes the algorithm ~45-60 seconds to make its recommendation. Still, surprise's famous SVD algorithm is super powerful and is worth checking out.

All EDA files are in the EDA folder. All files for the web-app are in the flask folder.

How to use

• Clone the repo
• Make sure you have the required libraries.
• Go to the flask directory in a terminal and run python application.py and follow the link to http://127.0.0.1:5000/

TO-DO

• Improve the bulky function
• Add scikit-learn alternative
• Deploy with Heroku