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.

Explore the machine learning development experience

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