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sgt102 OP t1_iwdedyf wrote

Reply to comment by Peantoo in [D] I Wrote a book "Managing Machine Learning Projects" by sgt102

Great question; very thought provoking!

I don't go through to in life CI/CD scenarios in the book, but I do look at running MAB's and A/B testing to understand the relative performance of models in live, and also write about the need for model monitoring and governance supporting the prod deployment.

Basically the book mostly ends with getting it into prod - but with the emphasis on getting it into prod with the right framework around it that it can be kept alive in prod.

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CaptMartelo t1_iwdkbco wrote

How the hell is it thought provoking. It's a yes or no question

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sgt102 OP t1_iwdwc7x wrote

Because it made me think about whether I should have extended the scope into the operational phases of a machine learning system?

So I found it thought provoking...

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globalminima t1_iwe6aeh wrote

The problem with most guides and even ML frameworks (e.g. MLFlow) is that they do everything pretty well up to deployment, and then offer only very basic options that are not really fit-for-purpose for intermediate or advanced systems. It's definitely the biggest differentiator between the best resources and everything else

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