Notebooks have become the worldwide standard environment for data scientists to work in.  It is very easy to get started, set up experiments and build models.  It is difficult however to go from an exploratory notebook to a fully operationalized model.  In this tutorial we will look at how to structure your workflow such that the same logic can easily be reproduced, the code be packaged and turned into a system that the business can rely on.

[Indaba𝕏SA] Spatialedge: Tutorial on Notebook workflows for reproducible data science