In "Explore the machine learning development experience", you mentioned re-training a few candidate replacement models before model integration. What's your process for deciding how many to try?
I tried architectures from other two scientific publications too. But then I decided to “re-work” a bit the architecture of the model I used in the session and decided to go with that.
The process can be different from model to model.