I posted a step-by-step tutorial that gives some hands on practice on Graph Neural Networks (GNNs) through a practical example using PyTorch framework and its geometric deep learning extension library "PyTorch Geometric".
I aimed to give some insights about what GNNs are, what type of problems they may solve and how graph datasets may look like.
The tutorial works on a social network dataset collected from GitHub. The post also shows how to construct graphs and visualize them using code and how to construct and train a simple GNN model for node classification task based on convolutional GNN . Here is the link.