Colab Notebooks and Video Tutorials

Official Examples

We have prepared a list of :colab:Colab notebooks that practically introduces you to the world of Graph Neural Networks with :pyg:PyG:

1. Introduction: Hands-on Graph Neural Networks <https://colab.research.google.com/drive/1h3-vJGRVloF5zStxL5I0rSy4ZUPNsjy8?usp=sharing>__
2. Node Classification with Graph Neural Networks <https://colab.research.google.com/drive/14OvFnAXggxB8vM4e8vSURUp1TaKnovzX?usp=sharing>__
3. Graph Classification with Graph Neural Networks <https://colab.research.google.com/drive/1I8a0DfQ3fI7Njc62__mVXUlcAleUclnb?usp=sharing>__
4. Scaling Graph Neural Networks <https://colab.research.google.com/drive/1XAjcjRHrSR_ypCk_feIWFbcBKyT4Lirs?usp=sharing>__
5. Point Cloud Classification with Graph Neural Networks <https://colab.research.google.com/drive/1D45E5bUK3gQ40YpZo65ozs7hg5l-eo_U?usp=sharing>__
6. Explaining GNN Model Predictions using <https://colab.research.google.com/drive/1fLJbFPz0yMCQg81DdCP5I8jXw9LoggKO?usp=sharing>__ :captum:null Captum <https://colab.research.google.com/drive/1fLJbFPz0yMCQg81DdCP5I8jXw9LoggKO?usp=sharing>__
7. Customizing Aggregations within Message Passing <https://colab.research.google.com/drive/1KKw-VUDQuHhMo7sCd7ZaRROza3leBjRR?usp=sharing>__
8. Node Classification Instrumented with <https://colab.research.google.com/github/wandb/examples/blob/master/colabs/pyg/8_Node_Classification_(with_W&B).ipynb>__ :wandb:null Weights&Biases <https://colab.research.google.com/github/wandb/examples/blob/master/colabs/pyg/8_Node_Classification_(with_W&B).ipynb>__
9. Graph Classification Instrumented with <https://colab.research.google.com/github/wandb/examples/blob/pyg/graph-classification/colabs/pyg/Graph_Classification_with_PyG_and_W%26B.ipynb>__ :wandb:null Weights&Biases <https://colab.research.google.com/github/wandb/examples/blob/pyg/graph-classification/colabs/pyg/Graph_Classification_with_PyG_and_W%26B.ipynb>__
10. Link Prediction on MovieLens <https://colab.research.google.com/drive/1xpzn1Nvai1ygd_P5Yambc_oe4VBPK_ZT?usp=sharing>__
11. Link Regression on MovieLens <https://colab.research.google.com/drive/1N3LvAO0AXV4kBPbTMX866OwJM9YS6Ji2?usp=sharing>__
12. Pooling in Graph Neural Networks with <https://colab.research.google.com/github/tgp-team/torch-geometric-pool/blob/main/docs/source/tutorials/hierarchical_gnns.ipynb>__ :tgp:null tgp <https://colab.research.google.com/github/tgp-team/torch-geometric-pool/blob/main/docs/source/tutorials/hierarchical_gnns.ipynb>__

All :colab:Colab notebooks are released under the MIT license.

Stanford CS224W Tutorials

.. image:: https://data.pyg.org/img/cs224w_tutorials.png :align: center :width: 941px :target: https://medium.com/stanford-cs224w

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The :stanford:null Stanford CS224W <http://web.stanford.edu/class/cs224w/>__ course has collected a set of graph machine learning tutorial blog posts <https://medium.com/stanford-cs224w>__, fully realized with :pyg:PyG. Students worked on projects spanning all kinds of tasks, model architectures and applications. All tutorials also link to a :colab:Colab with the code in the tutorial for you to follow along with as you read it!

PyTorch Geometric Tutorial Project

The :pyg:null PyTorch Geometric Tutorial <https://github.com/AntonioLonga/PytorchGeometricTutorial>__ project provides video tutorials and :colab:null Colab notebooks for a variety of different methods in :pyg:PyG:

1. Introduction [:youtube:null YouTube <https://www.youtube.com/watch?v=JtDgmmQ60x8>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial1/Tutorial1.ipynb>]
2. :pytorch:PyTorch basics [:youtube:null YouTube <https://www.youtube.com/watch?v=UHrhp2l_knU>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial2/Tutorial2.ipynb>]
3. Graph Attention Networks (GATs) [:youtube:null YouTube <https://www.youtube.com/watch?v=CwsPoa7z2c8>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial3/Tutorial3.ipynb>]
4. Spectral Graph Convolutional Layers [:youtube:null YouTube <https://www.youtube.com/watch?v=Ghw-fp_2HFM>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial4/Tutorial4.ipynb>]
5. Aggregation Functions in GNNs [:youtube:null YouTube <https://www.youtube.com/watch?v=tGXovxQ7hKU>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial5/Aggregation%20Tutorial.ipynb>]
6. (Variational) Graph Autoencoders (GAE and VGAE) [:youtube:null YouTube <https://www.youtube.com/watch?v=qA6U4nIK62E>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial6/Tutorial6.ipynb>]
7. Adversarially Regularized Graph Autoencoders (ARGA and ARGVA) [:youtube:null YouTube <https://www.youtube.com/watch?v=hZkLu2OaHD0>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial7/Tutorial7.ipynb>]
8. Graph Generation [:youtube:null YouTube <https://www.youtube.com/watch?v=embpBq1gHAE>__]
9. Recurrent Graph Neural Networks [:youtube:null YouTube <https://www.youtube.com/watch?v=v7TQ2DUoaBY>, :colab:null Colab (Part 1) <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial9/Tutorial9.ipynb>, :colab:null Colab (Part 2) <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial9/RecGNN_tutorial.ipynb>__]
10. DeepWalk and Node2Vec [:youtube:null YouTube (Theory) <https://www.youtube.com/watch?v=QZQBnl1QbCQ>, :youtube:null YouTube (Practice) <https://youtu.be/5YOcpI3dB7I>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial11/Tutorial11.ipynb>__]
11. Edge analysis [:youtube:null YouTube <https://www.youtube.com/watch?v=m1G7oS9hmwE>, :colab:null Colab (Link Prediction) <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial12/Tutorial12%20GAE%20for%20link%20prediction.ipynb>, :colab:null Colab (Label Prediction) <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial12/Tutorial12%20Node2Vec%20for%20label%20prediction.ipynb>__]
12. Data handling in :pyg:PyG (Part 1) [:youtube:null YouTube <https://www.youtube.com/watch?v=Vz5bT8Xw6Dc>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial14/Tutorial14.ipynb>]
13. Data handling in :pyg:PyG (Part 2) [:youtube:null YouTube <https://www.youtube.com/watch?v=Q5T-JdyVCfs>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial15/Tutorial15.ipynb>]
14. MetaPath2vec [:youtube:null YouTube <https://www.youtube.com/watch?v=GtPoGehuKYY>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial13/Tutorial13.ipynb>]
15. Graph pooling (DiffPool) [:youtube:null YouTube <https://www.youtube.com/watch?v=Uqc3O3-oXxM>, :colab:null Colab <https://colab.research.google.com/github/AntonioLonga/PytorchGeometricTutorial/blob/main/Tutorial16/Tutorial16.ipynb>]