jakubpeleska/redelex
ReDeLEx is a Python framework for developing and evaluating RDL models on relational databases via RelBench and CTU datasets.
This framework helps data scientists and machine learning researchers efficiently build and test deep learning models on complex relational databases. It takes a relational database (like PostgreSQL or MySQL) and transforms it into a graph representation, then applies various graph neural networks or other deep learning architectures. The output is a trained model capable of making predictions on tasks like classification or temporal events.
Use this if you need to develop, benchmark, and compare deep learning models on structured relational data for tasks like predicting outcomes or understanding relationships within your database.
Not ideal if your data is unstructured, purely tabular without meaningful relationships between tables, or if you only need classical machine learning models without exploring deep learning on graphs.
Stars
20
Forks
6
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Mar 05, 2026
Commits (30d)
0
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