A curated repository helps readers discover machine learning and AI courses published on YouTube.
Open source
24 alternativesML Course Notes
A collaborative collection shares course and lecture notes on machine learning, natural language processing, and AI.
About ML Course Notes
ML Course Notes is a GitHub repository where contributors share lecture notes on machine learning, natural language processing, and AI. Notes are organized by course. The listed courses include Andrew Ng's Machine Learning Specialization (2022), MIT 6.S191 Introduction to Deep Learning (2022), CMU Neural Nets for NLP (2021), CS224N: Natural Language Processing with Deep Learning (2022), CS25: Transformers United, and Andrej Karpathy's Neural Networks: Zero to Hero. A miscellaneous section covers diffusion models and reinforcement learning from human feedback (RLHF).
Entries are labeled as either complete or WIP (work in progress). Contributors are asked to open an issue before writing notes for a lecture to avoid duplicate work.
Key features
- Lecture-level notes grouped under named university and industry courses
- Topics include neural networks, word vectors, transformers, and deep reinforcement learning
- Links from each course section to its original course website
- Work-in-progress labels showing which lecture notes are unfinished
- Contribution process: open an issue, write notes, then submit a pull request
- Discord server linked for contributors and discussion
Best for: Learners and practitioners studying machine learning or NLP who want lecture-level study notes from the listed courses, and contributors who want to add notes to the collection.
Good for
- Notes are organized by course and lecture, which makes specific topics easy to locate
- WIP labels show which entries are unfinished
- Asking contributors to open an issue first is meant to prevent duplicate work
Watch out for
- Several lectures are marked WIP, so their notes are incomplete
- The excerpt does not state the license that applies to the notes
- Coverage depends on what contributors have written, so some listed lectures have no notes yet
ML Course Notes at a glance
- Category
- Education & Learning › Learn to Code
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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ML Course Notes FAQ
How do I contribute notes?
Identify a course and lecture from the list and open an issue to indicate you are working on it. Write your notes in a Google document, Notion document, or GitHub repository, revise them, and then open a pull request.
Where can I ask questions?
You can open an issue or contact the maintainer on Twitter. The repository also links to a Discord server.
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Tell us and an editor will check it.
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