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I wrote a similar guide based on my experiences:

https://austingwalters.com/neural-networks-to-production-fro...

I’ve gone through this guide and other guides before, as I often teach courses like: “introduction to deep learning”

The guide from fast.ai is very good and highly recommend. I also recommend if you want to get into deep learning taking a numerical methods course / guide. Once you understand the basics the hard part is understanding the pitfalls introduced from hardware (and some software) limitations




Is there a catalog of things that will bite you in this field?




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