Tutorials for Machine Learning on Graphs
Graph machine learning provides a powerful toolbox to learn representations from any arbitrary graph structure and use learned representations for a variety of downstream tasks. These tutorials aim to:
Recent versions of NumPy, PyTorch, PyTorch Geometric and Jupyter are required.
All the required packages can be installed using the following commands:
git clone https://github.com/mims-harvard/graphml-tutorials.git
cd graphml-tutorials
chmod +x install.sh && ./install.sh
conda activate graphml_venv
Pull requests are welcome.