Event language
UI language
Most data scientists work in jupyter notebooks, but the code have to be heavily refactored and optimized before it's ready for production. This is because research coding style is different than production coding style, and that data scientists might not be aware of proper software engineering practices, which lead to inefficient code.<br><br>There are a lot of gotchas to keep in mind when porting code written in jupyter notebooks to production-grade python project, we are going to discuss how to make it less painful for everyone involved.<br><br>Case in point: I tell data folks import the production project into notebooks, they can modify the code in vscode/etc and run interactively in the notebook, because if you manually copy the code over to notebook for debugging/dev, you might forgot to update all changes back to the python project. Data scientists: just copying the code over what can go wrong?
