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If you fit one of these profiles, this article is for you: ● You are a data science manager. You’d like to learn what happens downstream: How your model turns into a product.
This is the most “panoramic” picture I’ve seen if you are trying to understand the AI/ML pipeline from alpha to omega.
You can also get this content in many other places, but this is a well-organized and succinct presentation: The discussion around debugging DL models was particularly good: Get your model to run, overfit a single batch and compare to a known result.
A lot of this material was created in 2018 and is starting to show its age.
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