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3min chapter
Jordan Edwards: ML Engineering and DevOps on AzureML
Machine Learning Street Talk (MLST)
Reproducibility
More than anything else, you need to have reproduceability. You needto be able to lock down how was this model created. And the second thing is, in these re training work flows, we want to be able to recreate the model again without the datus oret. I think its tere actively creating exactly it's reproduce ability. It's also compose ability, though. O the next step, i think timwill will get to this in a subsequent slide, but is ok, right? So i have, i have,. i have a reproducable model. Now the m l engineer needs to be ableTo take that model, package it, certify it and then release it
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