| .. | ||
| docker | ||
| git | ||
| github | ||
| huggingface | ||
| papers | ||
| python | ||
| pytorch | ||
| README.md | ||
Reference
Background material to dip into when your project pulls you toward something you don't yet know. None of it is required reading. The class is driven by your project; this folder exists so that when a project hits a wall, there's something concrete to point at.
There are two flavors of reference here, and they're meant to be used differently.
Tools and tech (hands-on)
Short, self-paced primers on the things you'll most often end up touching. Read them when you have a reason to, not before.
| Folder | What it covers |
|---|---|
python/ |
Python basics — enough to read and tweak the code AI writes for you |
git/ |
Tracking changes, undoing mistakes, working on more than one thing at once |
github/ |
Putting code somewhere others (or future-you) can find it |
huggingface/ |
Where most open-weight models live; how to grab one and use it |
pytorch/ |
The framework most modern models are written in |
docker/ |
Running other people's software without polluting your own machine |
More will appear here as projects surface the need for them.
Papers (reading)
A small, opinionated set of papers that, taken together, give you a feel for how we got here. Skim them, read the abstracts, or just look at the dates and the names — the trajectory matters more than any individual result.
See papers/.
How to use this folder
- Don't binge it. Reading reference material in the abstract is the slowest way to learn it. Wait until your project gives you a reason.
- Skim, then dive. Read the README of a topic before reading any of the lessons. You may find you only need one section.
- Ask AI as you go. These primers are starting points, not textbooks. If something doesn't click, paste the snippet at an AI and ask.