[fsavard]

It's a theme I like to read about (I mean "practical issues around ML in production settings"). I find company blogs and some research publications are great resources. Examples:

- https://eng.uber.com/ - https://code.fb.com/

and many more. Google also publishes papers on various engineering practices obviously, some ML-related, but I can't find a blog where they focus on that specifically.

Also it's not "to keep up to date", but there's a great paper (from Google) that's often cited:

Machine Learning: The High Interest Credit Card of Technical Debt https://ai.google/research/pubs/pub43146

It talks about issues you face over the long run (I've experienced some of those). It also provides interesting pointers for further reading, e.g. about "pipeline jungles".

If others have pointers, I'm curious to hear about them as well.