Ask HN: How do you decide to release a new ML model in production? I am an ML engineer and have my own workflow that I use now and an aspirational workflow that I want to use. But I was curious how other ML engineers make this call. Here are some options to kickstart your thinking:
a) Release it if it performs well in offline training
b) A/B test in production alongside existing model(s)
c) Use contextual bandits in production
d) Some other way (details appreciated :-) ) |
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