Machine Learning & AI

An awesome list of awesome YouTubers that teach about technology. Tutorials about web development, computer science, machine learning, game development, cybersecurity, and more.

Markdown

7,662 stars

pushed 2026-08-05

src-d/awesome-machine-learning-on-source-code

Cool links & research papers related to Machine Learning applied to source code (MLonCode)

6,620 stars

pushed 2020-12-03

jphall663/awesome-machine-learning-interpretability

A curated list of awesome responsible machine learning resources.

4,052 stars

pushed 2026-06-03

grananqvist/Awesome-Quant-Machine-Learning-Trading

Quant/Algorithm trading resources with an emphasis on Machine Learning

3,941 stars

pushed 2025-05-21

krishnakumarsekar/awesome-quantum-machine-learning

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

HTML

3,631 stars

pushed 2024-05-07

paperswithcode/releasing-research-code

Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)

2,957 stars

pushed 2023-05-19

What this list looks like at a glance

These 10 repos carry 86,294 GitHub stars between them. EthicalML/awesome-production-machine-learning leads with 20,835, and the smallest here, paperswithcode/releasing-research-code, has 2,957. That spread is normal for awesome-lists: a topic usually has one or two lists everybody links to, then a tail of narrower ones that cover a corner the big list skips.

3 of the 10 were pushed to within the last year as of the 2026-08-10 snapshot. Star count tells you how many people bookmarked a list, not whether anyone still maintains it, so the push date is the more useful number when you are deciding which one to actually follow. Our guide on how to tell if a repo is still maintained covers what else to check.

New to the format? Read what a GitHub awesome list is. Wondering whether a repo above is still active? Seehow to tell if a GitHub repo is still maintained.