# Machine Learning with Graphs
#### [Home](https://hackmd.io/@DogChen/BJBTy7_T9)
---
## Note
- [Introduction](https://hackmd.io/@DogChen/rJOrvM_pq)
- [Traditional Feature-based Methods](https://hackmd.io/@DogChen/HyMXMxYTq)
- [Node Embeddings](https://hackmd.io/@DogChen/rkFNrtt6c)
- [Graph as a Matrix](https://hackmd.io/@DogChen/BkBDXiJAq)
- [Message Passing and Node](https://hackmd.io/@DogChen/HkV8wTxCc)
- [Graph Neural Networks(GNNs)](https://hackmd.io/@DogChen/S1sIOEMCc)
- [GNN framework](https://hackmd.io/viumB90_SNCJIxOBPa0jjQ?view)
- [GNN Augmentation & Training](https://hackmd.io/xwkVFvYIRfinjqtiGICOig?view)
- [Expressive Power of GNN](https://hackmd.io/LnkBWsMzQbe_nAMQ_-r4lQ?view)
## Resource
* http://snap.stanford.edu/class/cs224w-2020/
{"metaMigratedAt":"2023-06-17T06:10:32.399Z","metaMigratedFrom":"YAML","title":"Machine Learning with Graphs","breaks":true,"contributors":"[{\"id\":\"07be3cd1-5245-45b1-9024-6c142e61f375\",\"add\":889,\"del\":327},{\"id\":\"54ad384e-8125-4d94-83f2-f774d86b8f19\",\"add\":214,\"del\":0}]"}