ramikrispin,
@ramikrispin@mstdn.social avatar

(2/3) The course includes 47 lectures, and it covers topics such as:
✅ ML applications for graph
✅ Graph neural networks (GNN)
✅ Knowledge graph completion
✅ Recommendation with GNN
✅ Geometric deep learning
✅ Link prediction and causality

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