A Practical Guide to Graph Neural Networks

Graph neural networks (GNNs) have recently grown in popularity in the field of artificial intelligence due to their unique ability to ingest relatively unstructured data types as input data. Although some elements of the GNN architecture are conceptually similar in operation to traditional neural networks (and neural network variants), other elements represent a departure from traditional deep learning techniques. Importantly, we present this tutorial concisely, alongside worked code examples, and at an introductory pace, thus providing a practical and accessible guide to understanding and using GNNs.