ML Architecture Musings
After some deliberation, I’ve decided to brain dump ideas I have on structuring an industrial ML environment. Some of these ideas might be good, a lot of them are probably inefficient, and a couple might be pretty bad. Of course, making mistakes is part of the learning process, which is why I made the mistake of using Jekyll instead of a Tedium blog (I kid, I kid).