The November 2024 paper introduces GNN101, an open-source, web-based interactive visualization tool designed to help non-experts learn about Graph Neural Networks (GNNs), whose complex nature often challenges beginners. This educational tool addresses limitations in existing resources by seamlessly integrating mathematical formulas with visualizations across multiple abstraction levels, from a model overview to detailed matrix calculations. GNN101 features complementary views—a node-link diagram for intuitive graph understanding and a matrix view for a comprehensive feature overview—to illustrate how GNNs process graph data and update node features. The authors detail the design goals, implementation, and initial deployment of GNN101, showing its usability and effectiveness in making GNN computations more intuitive and engaging for students. Source: https://arxiv.org/html/2411.17849v1