Most of my projects start life in a Jupyter notebook. The interesting part begins when someone else needs to use them.
A short checklist
- Freeze the preprocessing so training and serving agree.
- Wrap the model in a small FastAPI service.
- Add a simple front-end so people can try it without reading code.
- Log inputs and predictions so you can see how it behaves in the wild.
A model nobody can run is just a very expensive screenshot.