#NetworkX

TypeDB-ML provides integration options for graph algorithms and machine learning within TypeDB, utilizing tools like NetworkX and PyTorch Geometric. It supports building customizable Graph Neural Networks for data in TypeDB and facilitates efficient graph-based data manipulation for link prediction. The platform offers diverse querying and encoding features, complemented by resources for effective data management within TypeDB. Learn through practical examples about maximizing data utility with Graph Neural Networks.

This guide provides an objective introduction to graph deep learning, combining insights from prominent works and university courses. Covering basic concepts, graph neural networks, and practical code using frameworks like NetworkX, DGL, and PyG, it's suitable for beginners and offers theoretical and practical exercises. Future updates will include applications in different fields, ensuring a comprehensive resource for those keen on graph deep learning advancements.