The model development pipeline is still a far cry from the maturity of the software development pipeline, and will have to get there in order to reduce the hand

The model development pipeline is still a far cry from the maturity of the software development pipeline, and will have to get there in order to reduce the hands-on heavy lifting required for model development and deployment. Along with packaging a trained model are things like: Snapshot/versioning of the training and test data used to create the model, versioning of the model, storing versioned models in a model registry, auto-deploying models from the registry to target environments, telemetry from deployed models. Closest I've found is https://github.com/mitdbg/modeldb https://github.com/mitdbg/modeldb, and I've spoken to the woman leading the effort. They still have data versioning as an open question, and don't see the need. But there are training set modification, results RCA, and other use cases that drive the need to catalog training/test data with the model that results. It'll get there. Just a question of when and how.