SQL4NN: Validation and Expressive Querying of Models as Data

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 argue that relational database systems and SQL can be well suited for many such tasks.