Introduction

This repository has been forked from A Practical Guide to Graph Neural Networks, which contains the code for the extended examples in the paper "A Practical Guide to Graph Neural Networks".

Folder structure

.
├── notebooks       # The .ipynb files of the example code
├── .gitignore                     
├── requirements.txt         # The pip requirements file
├── LICENSE
└── README.md

Running on your own computer

To run the code, install the requirements with pip install -r requirements.txt, preferably creating before a conda-based environment with the following command:

conda create -n gnn_tutorial python==3.8
conda activate gnn_tutorial
pip install -r requirements.txt

After these operations run the jupyter notebook command.

This code has been tested using Python 3.8.0.