Have been learning Machine Learning concepts and doing hands-on past few months. Now got a bit different doubt than implementation of code.

This is regarding measures to be considered while deploying in a Prod environment, say something like "A newbie's checklist to ML production" example -

  • Are Feedback loops always considered?
  • Is cross-validation done in final prod model or only during train/test the model?
  • How the auto-suggestion in Amazon or any ecommerce website works? - Meaning does the model get trained on every page load or already pre-trained and just predicts (suggests) based on user selections?

I know the questions are too general and newbie, but will help many to understand the concepts relating to real-world. Please advise.

Let me know for any further information and I will be happy to furnish/respond.


1 Answer 1


I got some pointers (below links) to my doubts. Hope it helps other future readers as well.

Will keep updating this space as and when I get some good answer(s) regarding this.


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