Anime Recommender

An autoencoder based recommender system trained to curate anime recommendations for MyAnimeList users. Users may enter their MAL usernames into a website, with a VueJS frontend and Flask backend, that processes their anime lists (obtained via the MAL API) to generate anime recommendations.

Demo

The Model

The architecture of the recommender system model was inspired by the Autorec paper which uses autoencoders to perform collaboriative filtering. Training was done using PyTorch on Google Colaboratory's hardware.

The dataset for the model was obtained by aggregating, cleaning and preprecessing the following Kaggle datasets

• Anime Recommendation Database 2020
• MyAnimeList Anime and Manga Datasets

using Pandas.

Installation

To run the project locally, npm 8.18.0 and conda 22.9.0 are required before performing the following steps.

1. Clone the application

git clone https://github.com/edweenie123/anime-recommender.git
cd anime-recommender

2. Install required Python packages onto a conda environment

conda create --name <env> --file requirements.txt

3. Run the Flask server by cd-ing into web/server and running

flask run

NB: Make sure to create a config.py file in web/server containing your MAL API access token

4. Run the VueJS development server by cd-ing into web/client and running

npm run dev