MRMrCoffee7·Jul 27, 2025
This awesome-math Github repo has a large list of many learning resources https://github.com/rossant/awesome-math
In Ask HN: Where do mathematicians/physicists hang out? / How to learn math?rossant
awesome-math
Python2018–2025
rossant / awesome-math
awesome-math
A curated list of awesome mathematics resources
11Distinct people
12Mentions
0Explicit recommenders
17KGitHub stars
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What it is
A curated list of awesome mathematics resources
GitHub
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Also in these discussions
- sindresorhus/awesome · linked in 2 of the same discussions
Mentioned in the same Hacker News threads. That is not proof they are substitutes.
This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by year12 dated mentions
Observed mentions: 2018-01-07 11:37:24 UTC to 2025-07-27 01:26:21 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 2 | 1 | 1 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 3 | 0 | 3 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 2 | 2 | 0 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 3 | 1 | 2 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
12 sourcesAsk HN: Programmers Who Want to Get Better at Math
I have some questions for programmers and software engineers who feel they're not good enough at math and want to improve, particularly with the goal of applying math to their current or future jobs, or who consider a career change. This might include fields like ML/AI, data science, graphics programming, video games, physics simulations, scientific and numerical computing, crypto, finance, signal processing, etc.
As the creator of the Awesome Math resource [1], I'm looking to gather and organize math resources specifically for those who fit this description. If that's you, what are your main challenges? Why does math feel difficult? Do you struggle with math notation, similar to how adult musicians without formal training can find modern music notation difficult? What stops you from picking up a math textbook and working through it? Have
Read the rest
you ever tried that? What alternatives to traditional textbooks would work better for you?
If you had to go back to the basics, what level would you start from? High school? Middle school? Elementary school? For example, are you comfortable with elementary algebra [2]—solving linear and quadratic equations, simplifying algebraic expressions with fractions and powers, etc.? If not, is this something you feel you need to master before moving on to more advanced math topics?
If you could have a kind of survival guide before progressing to more advanced resources, what would you want included? What would be unnecessary? What topics would you want clearly explained? Which areas of math would you like covered—linear algebra, calculus, geometry, arithmetic, probability theory, combinatorics, something else? Do you know of any such guides? If you've tried them, what did you like about them, and what could be improved?
Feel free to respond here, but if you'd like to stay in touch as I continue developing this long-term project, please also send me an email (see profile) and let me know what you're interested in. I may reach out again later as I make progress.
[1] https://github.com/rossant/awesome-math
[2] https://en.wikipedia.org/wiki/Elementary_algebra
Shameless plug. See also https://github.com/rossant/awesome-math
In Open Mathematics DepositoryOne of the few times I wish we had dms here. :) I do not have many groups to offer, but for educational resources, here you go... Dig around on GitHub for Awesome Lists. There is so much out there:
- https://github.com/sindresorhus/awesome#learn
- https://github.com/mike-north/awesome-learn-to-code
- https://github.com/lauragift21/awesome-learning-resources
- https://github.com/afontcu/awesome-learning
- https://github.com/yrgo/awesome-educational-games
- https://github.com/notpresident35/awesome-learn-gamedev
- https://github.com/RahulBirCodes/awesome-steam
- https://github.com/Ghassen-Chaabouni/machine_learning_games
- https://github.com/microsoft/Web-Dev-For-Beginners
- https://github.com/microsoft/ML-For-Beginners
Also check out this list Pitt puts out every year:
- https://github.com/SimplifyJobs/Summer2024-Internships
and make sure
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to ping www.skypeascientist.com for speakers.
More, maybe useful:
- https://github.com/freeCodeCamp/freeCodeCamp
- https://github.com/vinta/awesome-python
- https://github.com/DopplerHQ/awesome-interview-questions
- https://github.com/LeCoupa/awesome-cheatsheets
- https://github.com/josephmisiti/awesome-machine-learning
- https://github.com/awesomedata/awesome-public-datasets
- https://github.com/Roobyx/awesome-game-design
- https://github.com/dh-tech/awesome-digital-humanities
- https://github.com/bytecauldron/awesome-gamemaker
- https://github.com/academic/awesome-datascience
- https://github.com/awesome-foss/awesome-sysadmin
- https://github.com/qinwf/awesome-R
- https://github.com/rossant/awesome-math
- https://github.com/newTendermint/awesome-bigdata
- https://github.com/luong-komorebi/Awesome-Linux-Software
- https://github.com/ChristosChristofidis/awesome-deep-learnin...
- https://devhints.io/
I'll make another comment if I find anymore in my bookmarks. I'm also an educator.
A curated list of mathematics resources
3 points · Open discussionSomething like this https://github.com/rossant/awesome-math ?
In Introduction to Linear Algebra for Applied Machine Learning with PythonAnd, of course, let's not forget:
- Free Computer Science degree-like path at [1]
- Free collection of Math resources at [2]
As a self-taught person, I recently started attending a college for computer science. I don't need the degree, but I wanted the knowledge. Granted, I'm just at the end of 1st year, but a lot of what is being taught is nothing more than giving formal definitions and formal names of things I've already taught myself.
So, I truly believe there are so much free good education out there for you. All you have to do is have the right mindset to get it.
[1] https://github.com/ossu/computer-science
[2] https://github.com/rossant/awesome-math
In A curated list of Computer Engineering resources3blue1brown is a special kind of awesome.
I'd love to filter the internet by "content that can give you insights right now that would otherwise take years of study in a specific discipline to even know exists".
Another that I saw recently on an HN comment (thanks tptacek) is https://www.youtube.com/watch?v=nfY0lrdXar8
A quick google for "3blue1brown awesome github" (my usual strategy for finding good similar content) landed me here: https://github.com/rossant/awesome-math
The awesome lists are pretty good starting points for finding good content, but there's a ton of them of variable quality, so you end up with stuff like this: https://github.com/jonatasbaldin/awesome-awesome-awesome (which has 68 forks...)
In Ask HN: Best resources to gain math intuition?There are some awesome resources on github on many topics including math. Just search for "github awesome-X" like https://github.com/rossant/awesome-math
And here is a root project for all resources
https://github.com/sindresorhus/awesome
Personally I'd like to have something like a learning path. Not only a list of resources/topics but also some guide how to approach the learning process. O'Reilly has something like this but it's not mature yet https://www.safaribooksonline.com/learning-paths/ in my opinion.
MIT OCW has some guide for prequesities https://ocw.mit.edu/courses/mit-curriculum-guide/#map
I hope that helps you
In Ask HN: How to self-study mathematics from the undergrad through graduate level?A lot of resources on the awesome github: https://github.com/rossant/awesome-math
(from https://github.com/sindresorhus/awesome)
In Ask HN: How do I learn math/physics in my thirties?