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- drop "detective at a scene, not a fortune teller", "guess wearing a fix's clothes", "that reflex is the enemy" - rephrase negative parallelisms in intro/calibrate/loop to positive (judgment not a checklist; mindset not ticking boxes; evidence not prior; isn't a recipe; it's a; menu not a procedure; code not abstract) - keep genuine instructional contrasts (relative error not absolute, etc.) - trim pseudocode comments to intent-only Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
ML Debugging Folklore
Practitioner knowledge for debugging ML systems, curated and synthesized by wassname. Opinionated by source selection -- I picked sources I trust (Schulman, Goodfellow, CS231n, ...) and had an LLM extract the most relevant information for debugging ML systems.
Use as a Claude skill
/skills add https://github.com/wassname/ml_debug
Or paste SKILL.md into your system prompt / context when debugging.
What's here
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SKILL.md -- the main artifact. Load into an LLM agent's context as a debugging skill. Parts 1-5 are reference knowledge; Part 6 is a runnable triage protocol (grep patterns, diagnostic snippets, decision tree); Part 7 is debugging mental models and practitioner priors.
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docs/evidence/ -- frozen local copies of source material (blog posts, talks, papers, reddit threads). Claims in SKILL.md link back to exact quotes here.
Description
skill for debugging and dev of machine learning, collected over the years in an attempt to uplift agents (and myself)
3.7 MiB
Languages
Python
99%
Just
1%