We consider machine learning models, learned from data, to be an important, intensional, kind of data in themselves. As such, various analysis tasks on models can be thought of as queries over this intensional data, often combined with extensional data such as data for training or validation. We demonstrate that relational database systems and SQL can actually be well suited for many such tasks.
@article{arxiv.2502.14745,
title = {SQL4NN: Validation and expressive querying of models as data},
author = {Mark Gerarts and Juno Steegmans and Jan Van den Bussche},
journal= {arXiv preprint arXiv:2502.14745},
year = {2025}
}