This repository provides Jupyter Notebook implementations of classic graph neural network papers as a supplement to an accompanying blog series. It covers DeepWalk for node embeddings, Graph Convolutional Networks for semi-supervised learning, GraphSAGE for inductive node classification, ChebNet using Chebyshev polynomials for spectral convolution, and Graph Attention Networks with attention mechanisms for graph representation learning.