[D] How is test-driven development implemented in the context of machine learning?

I recently tried to refactor a previous project that I had, but I realized that after making all of the changes the performance wasn't reproducible anymore. I decided to start from scratch, make incremental changes, and make sure that the model's performance is maintained with each change. Very basic in hindsight, but I guess I was too hasty with coding.

Anyway, running the full model's training and evaluation with each change is proving to take too long. I'm curious if …

change context development incremental machine machine learning machinelearning making performance project test test-driven development