This repository contains Jupyter Notebook and Python implementations of graph neural network concepts from a Chinese book on GNN principles. It covers foundational architectures including Graph Convolutional Networks for node classification, GraphSAGE for sampling-based neighborhood aggregation, graph autoencoders for representation learning, and graph-level classification. All implementations use PyTorch.