What is ml-youtube-courses?

This repository is not a piece of software but an organised directory of free machine learning and AI courses available on YouTube. It is maintained by DAIR.AI, a group that says it loves open AI education, and its purpose is to make it easier to find good, recent video courses on a wide range of ML topics in one place rather than hunting around YouTube yourself. The list is structured by subject area. Under Machine Learning you will find university courses such as Caltech CS156: Learning from Data, Stanford CS229, MIT 6.S897 on machine learning for healthcare, and probabilistic and statistical machine learning lectures. The Deep Learning section gathers Andrej Karpathy's Neural Networks: Zero to Hero series, Stanford CS230, MIT introductions to deep learning, CMU's 11-785, NYU's deep learning course, and others. There are dedicated sections for Natural Language Processing (including Stanford CS224N, Stanford CS25 on transformers, the Hugging Face NLP course, and CMU Advanced NLP), Computer Vision (including Stanford CS231N), Reinforcement Learning (with the DeepMind lecture series and Stanford CS234), Graph Machine Learning, Multi-Task and Meta-Learning, and practical topics such as MLOps, prompt engineering, LangChain, and full-stack LLM bootcamps. Each entry lists the lecture topics covered and links to the relevant YouTube playlist. Someone would actually use this if they want to teach themselves machine learning or a specific subfield like NLP or computer vision without paying for a platform, or if they want a quick way to see what is being taught at universities like Stanford, MIT, CMU and Caltech. The full README is longer than what was provided.