This is a minor update of the "Little Book of Deep Learning", a phone-formatted free book for people with a STEM background that happened to be quite popular (580k+ download in a year).
This update adds in particular a chapter about methods to run or fine-tune LLMs with limited compute and memory (prompt engineering, quantization, low-rank adapters, and model merging).
This update adds in particular a chapter about methods to run or fine-tune LLMs with limited compute and memory (prompt engineering, quantization, low-rank adapters, and model merging).