05 - Graph Attention Network (GAT) explained | step-by-step

0:00 Update equations for GCN, GraphSage and GAT 5:34 GAT from scratch 19:00 Train and test 24:45 GAT from dgl In this video, we go through the steps in creating a simple graph attention network with Graph Attention Convolution (GATConv) layers. We will create a GNN model in which GATConv is implemented from scratch, train it and compare its performance with the exact same model which uses the built-in GATConv from DGL. If you enjoyed this video, please press the 👍 button. That would mean a lot for me to make future videos. As always, feel free to drop a comment down below. Source code: https://github.com/dtdo90/Deep_Graph_... --------------------------------------------------------------------------------------------------------------------------------------------- 📞 Connect with Me: 👉 LinkedIn:   / tai-do-9463002b7   🤖 Github: https://github.com/dtdo90 --------------------------------------------------------------------------------------------------------------------------------------------- Start your AI Career here: https://nicolai-nielsen-s-school.teac...