# Colab Notebooks and Video Tutorials

## Official Examples

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

All Colab notebooks are released under the MIT license.

## Stanford CS224W Tutorials

The Stanford CS224W course has collected a set of graph machine learning tutorial blog posts, fully realized with PyG. Students worked on projects spanning all kinds of tasks, model architectures and applications. All tutorials also link to a Colab with the code in the tutorial for you to follow along with as you read it!

## PyTorch Geometric Tutorial Project

The PyTorch Geometric Tutorial project provides **video tutorials and** **Colab notebooks** for a variety of different methods in PyG:

(Variational) Graph Autoencoders (GAE and VGAE) [ YouTube, Colab]

Adversarially Regularized Graph Autoencoders (ARGA and ARGVA) [ YouTube, Colab]

Graph Generation [ YouTube]

Recurrent Graph Neural Networks [ YouTube, Colab (Part 1), Colab (Part 2)]

DeepWalk and Node2Vec [ YouTube (Theory), YouTube (Practice), Colab]

Edge analysis [ YouTube, Colab (Link Prediction), Colab (Label Prediction)]