# Notes on ML, systems, and the occasional math rabbit hole
Most ML papers throw math at you and call it an explanation. Here's how I actually developed intuition for why constraining weight updates to a low-rank subspace makes fine-tuning so efficient.
An OS course sounds irrelevant to application-level engineering. It isn't. Here's the mental model I built that changed how I think about every concurrent system I touch.
A postmortem on building a grade distribution visualizer for Berkeley students — the interesting data pipeline problems, the D3.js lessons, and the one query that took 45 seconds before I fixed it.