Graph Neural Networks (GNNs) are one of the most interesting architectures in deep learning but educational resources are scarce and more research-oriented.
In this course, you'll learn everything you need to know from fundamental architectures to the current state of the art in GNNs.
| Chapter | Description | Article | Notebook |
|---|---|---|---|
| 1. Introduction to Graph Neural Networks | What's a GNN? Essentials of graph theory with PyTorch Geometric. | Article |  |
| 2. Graph Attention Network | Implement a GNN with self-attention to classify nodes on CiteSeer. | Article | |
| 3. GraphSAGE | Scale GNNs with mini-batching and the GraphSAGE architecture on PubMed. | Article | |
| 4. Graph Isomorphism Network | Maximize the power of the GNN for graph classification on PROTEINS. | Article | |
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