@jeremy if this isn’t an appropriate title or the post, feel free to move or remove If folks want to edit and clarify any points below, I think that would be helpful for everyone to be in the best position possible before class on 10/30.
Day Zero Checklist
… or, what you should have ready to go by day 1 of class:
Bash/Terminal client
Git client
A development environment for machine learning (AWS, Paperspace, and/or your own rig)
AWS
Pros: What your employer is likely using, special treats (maybe), heavily documented.
Cons: More expensive, inferior GPUs (for now)
Paperspace
Pros: Easy to use, GUI or Terminal views, better GPUs than AWS, a fast.ai VM ready for use, $15 credits
Cons: Less flexible than AWS, more expensive in the long run than own machine
Crestle
Pros: Easiest to use, all fast.ai software installed and ready to use, can switch between cheap non-GPU and full GPU instance quickly
Cons: A bit slower than other options; no ability to ssh directly in (although can use web-based terminal)
Your own machine
Pros: Can be configured with superior hardware to cloud options, cheaper in long run.
Great! Thanks. I edited the title, since this isn’t actually a wiki (i.e. editable-by-all) thread, and added Crestle, plus made a few changes.
Most importantly, I removed the bit about cloning fastai repo locally. For most people, there’s no reason to do that (unless you have an Nvidia GPU of your own).
If you want to make it part of the wiki for folks to edit I think that would be nice; either way, I think lists like this go a long way in making day 1 of anything go smoother.
I’m planning to add some links when I get home and review my notes from the Saturday workshop.