GitHub repos for math provide structured learning from basics to advanced topics.
Interactive tools turn complex math concepts into hands-on, practical exercises.
Open-source resources make advanced math and ML accessible to all learners.
Mathematics is one of the core aspects of data science, machine learning, physics, and finance. Having the right self-study tools can help learners understand concepts and their applications very easily. GitHub hosts multiple high-quality repositories that offer structured curricula, visualizations, resources, and exercises for both beginners and experts.
Below are ten GitHub projects worth considering in 2025 for honing mathematical skills:
OSSU/math stands for Open-Source Society University's math curriculum. It is a self-paced, degree-level program.
Why It Matters: Offers a complete foundation covering algebra, analysis, modern algebra, topology, and more. The roadmap uses free courses and textbooks, making the GitHub repo a strong option for serious learners.
Awesome-Math is a curated list of some of the best online mathematics resources.
Why It Matters: The list covers number theory, probability, algebra, differential equations, and more. For learners who like exploring specific topics, this repo contains the best textbooks, lecture notes, and visual tools.
Also Read: Top 10 GitHub Repositories to Learn MLOps in 2025
The repository provides resources focused on the mathematics behind machine learning. This includes algebra, optimization, probability, topology, and other related fields.
Why It Matters: Students interested in ML or data science can take advantage of this repo by connecting theory with application. The project has a collection of books, research papers, and practice material.
TalalAlrawajfeh/mathematics-roadmap lays out a step-by-step path of learning mathematics, starting with the basics and moving toward advanced topics.
Why It Matters: Many learners lose direction without clear milestones. This project helps set goals and shows what to study next.
Modern-Math-Collection is a collection of modern math resources, including books, videos, and tools, sorted by topic.
Why It Matters: The open-source math learning resource offers variety for different learning styles. Whether through lectures or reading, it helps balance study methods and prevent burnout.
Also Read: Top 10 GitHub Repositories to Learn Backend Development in 2025
The GitHub repository provides a list of materials, algorithms, study notes, and code for the mathematics that drives machine learning and deep learning.
Why It Matters: As ML grows, understanding the mechanics becomes important. This repo covers gradient calculus, optimization, and the theory behind algorithms.
mXparser is an open-source mathematical expression parser and evaluator for Java, .NET, and more.
Why It Matters: It shows the computational side of math, explaining how expressions are solved programmatically. It is useful for understanding how math operations become code.
MathPartner is a cloud-based symbolic-numeric system using a custom Mathpar language. The project is available as open source on GitHub.
Why It Matters: Learners can use the project to write and share computable mathematical texts. This makes the link between formal mathematics and practical computation clearer.
An interactive textbook platform where math courses are authored in LaTeX and integrated with tools like GeoGebra and Desmos.
Why It Matters: The repository combines reading with hands-on learning. Interactive exercises and visualizations make concepts easier to understand, especially for learners who benefit from practice.
SuanShu Numerical Library is a Java library covering numerical analysis, including matrix operations, optimization, and statistics.
Why It Matters: Studying a numerical library shows how mathematical algorithms are implemented in real code. Concepts like eigenvalues or polynomial roots become clearer when seen in practice.
Here are some tips and tricks to help you with open-source math learning:
Make a Plan: Choose a roadmap like OSSU or TalalAlrawajfeh’s project and use other repos as support.
Active Learning: Work through exercises, re-create proofs, and write small programs. Ximera gives interactive practice, while SuanShu or mXparser provides ways to see how theory turns into code.
Cross-Discipline Connections: Use ML-focused repos to see how algebra, calculus, and probability connect directly to machine learning and data science.
Peer Learning and Revision: Join forums, contribute to awesome lists, and discuss with communities. Explaining a concept to others strengthens memory and understanding.
GitHub provides access to many open-source math resources. Learners can easily find repositories that provide structured paths for building a strong foundation, preparing for advanced research, or exploring the mathematics behind machine learning. These GitHub projects are great options for anyone looking for clear, practical, and well-organized study material.
1. Which GitHub repository is best for a complete self-paced math curriculum?
OSSU/math offers a full, structured program covering algebra, analysis, topology, and more for serious learners.
2. How can I learn math specifically for machine learning?
Mathematics-for-ML and krishnakumarsekar’s repos provide theory, algorithms, and practice linking math to ML concepts.
3. Are there interactive tools to practice math concepts online?
Ximera Project and MathPartner allow hands-on practice, visualizations, and symbolic computation for deeper understanding.
4. Can GitHub help with both theory and coding in math?
Yes, mXparser and SuanShu show how expressions and algorithms work in code, connecting theory to computation.
5. How should I structure my self-study using these repos?
Follow a roadmap like OSSU or TalalAlrawajfeh’s project, supplemented with exercises, code libraries, and interactive tools.