TypeDB-ML
A machine learning integrations library for TypeDB, enabling graph algorithms and Graph Neural Networks on strongly-typed graph data.
What is TypeDB-ML?
TypeDB-ML is a machine learning integrations library for TypeDB that enables graph algorithms and Graph Neural Networks (GNNs) on strongly-typed graph data. It provides tools to export TypeDB data to frameworks like NetworkX for graph analysis and PyTorch Geometric for building custom GNNs, solving the problem of applying advanced ML techniques to structured graph databases.
Data scientists and developers working with TypeDB who need to perform graph analysis, machine learning, or build predictive models on strongly-typed graph data, particularly those interested in Graph Neural Networks or graph algorithms.
Developers choose TypeDB-ML for its seamless integration with TypeDB's type system, support for heterogeneous data in PyTorch Geometric, and ready-to-use examples like link prediction, enabling ML on structured graph data without manual data conversion headaches.
Overview
TypeDB-ML is the Machine Learning integrations library for TypeDB
Use Cases
Best For
- Applying graph algorithms from NetworkX to TypeDB data
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