This course is a quick tour of machine learning on graphs. It will introduce the foundational concept of message passing and explain core algorithms, like Label Propagation, Graph Convolutional Networks and Graph Attention Networks. It will also show you how to implement a Graph Convolutional Network from scratch using only NumPy.
In addition to this lecture content, there is also a set of bonus videos that discuss cutting edge GNN research with the original authors. For example, we dive into work from Deep Mind with Jonathan Godwin on how they used GNNs to model complex physics simulators, and discuss industry applications with scientists from Twitter and Uber.