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 In an attempt to upskill the ML debugging on AI coding assistants (and humans), I've collected high quality sources on ML debugging and the mindset and the "taste". When I started ML I went searching for discussions on best practices, and started a few discussions of my own and they helped me a lot, I hope they can help others. This intro is human written, and the below is AI written with human guidance.
 
-Practitioner knowledge for debugging ML systems, curated and synthesized by [wassname](https://github.com/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.
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 ## Use as a Claude skill
 
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