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kmario23/deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
A large, hand-maintained index of free university lecture series covering deep learning, ML fundamentals, RL, NLP, computer vision, and related math. Essentially a bookmark list that someone spent real time assembling — 80+ courses from Stanford, CMU, MIT, Oxford, DeepMind, and others, spanning 2011–2022. For anyone starting out or filling gaps, it's a faster way to find high-quality video courses than searching YouTube.
The breadth is genuine — it covers foundational math (Gilbert Strang's linear algebra, 3Blue1Brown's calculus) alongside cutting-edge topics like geometric DL and graph neural networks, not just the obvious Coursera courses. The table format with direct YouTube playlist links and course webpage links side by side is actually useful — you can see who teaches it, when, and jump straight to the videos. It includes non-US universities (IIT Madras, ETH Zürich, TU München, University of Amsterdam) which surfaces courses that don't get the usual Twitter attention. The Python script for converting the markdown to a static HTML page is a practical touch that makes it hostable.
Maintenance stopped in late 2024 and the last real wave of additions was 2021–2022, so anything from the transformer/LLM era onward is mostly absent — no fast.ai v5, no Karpathy's nanoGPT lectures, nothing on diffusion models or RLHF. Many of the older course pages (pre-2018) are dead or require institutional login; the repo links to them anyway with no indication of what's broken. There's no rating, no note on which courses are actually good versus just famous, so a beginner has no signal to pick between 12 different 'Introduction to Deep Learning' entries. The HTML rendering via the included Python script is also clearly an afterthought — the output is functional but barely.