For a comprehensive platform for learning mathematics, the strongest matches are jushbjj/mr.-ranedeer-ai-tutor (Mr), google/latexify_py (latexifypy converts Python code into LaTeX expressions, making it) and shuhuai007/machine-learning-session (This project is a static documentation site presenting mathematical). katex/katex and udlbook/udlbook round out the shortlist. Each is ranked by relevance to your query, popularity and recent activity.
We curate open-source GitHub repositories matching “mathematical learning resources”. Results are ranked by relevance to your query — pick filters below to narrow, or refine with AI.
Mr. Ranedeer AI Tutor is an AI education framework and system prompt designed to transform a large language model into a personalized tutor. It uses a structured set of instructions to organize educational content into sequential modules and knowledge assessments for adaptive learning. The system features a persona template that allows for the adjustment of academic depth and communication tone to match a student's specific needs. It also provides multilingual support, enabling the tutor to switch instruction and output languages based on user preferences. The framework covers custom lesson
Mr. Ranedeer AI Tutor is an AI-powered education framework for personalised tutoring with adaptive learning, but it is not a dedicated mathematics platform and lacks built-in interactive problem sets, automated grading, and LaTeX support, making it a partial fit rather than a full interactive math learning tool.
latexify_py is a Python to LaTeX converter and mathematical expression generator. It functions as a code to math renderer that transforms Python source code, functions, and abstract syntax trees into formatted LaTeX mathematical expressions. The library focuses on code to equation conversion and mathematical expression rendering. It translates programming logic and algorithmic operations into professional LaTeX notation for use in technical documentation, academic papers, and research. The system provides capabilities for technical document automation and the ability to pretty-print function
latexify_py converts Python code into LaTeX expressions, making it a useful building block for displaying math, but it is not an interactive mathematics learning platform — it lacks problem sets, automated grading, progress tracking, and adaptive learning, and is a library rather than a self-hostable application.
This project is a machine learning educational resource and study site focused on the theoretical foundations and mathematical derivations of machine learning algorithms. It serves as a study guide for mastering the linear algebra, calculus, and proofs required for predictive modeling. The site functions as a markdown documentation portal and static site generator, converting formatted text and LaTeX formulas into a structured web interface. It utilizes a typesetting engine to render complex academic derivations and mathematical equations clearly within the browser. The platform includes a r
This project is a static documentation site presenting mathematical derivations for machine learning, which resembles a study guide rather than an interactive platform with problem sets, grading, or adaptive learning.
KaTeX is a typesetting library and web math renderer that transforms TeX and LaTeX mathematical notation into high-quality HTML and CSS for web browsers. It functions as a math notation parser and LaTeX to HTML converter, capable of operating as both a client-side library and a server-side math renderer to generate static HTML expressions. The project supports a wide range of specialized mathematical rendering, including chemical equation rendering, Bra-ket notation for quantum mechanics, and mathematical logic typesetting. It provides comprehensive controls for structural layouts such as mat
KaTeX is a math typesetting and rendering library, not an interactive learning platform—it handles LaTeX display but lacks problem sets, grading, progress tracking, or adaptive learning paths.
udlbook is a deep learning educational repository and a collection of interactive learning notebooks designed for studying neural network architectures. It serves as a digital repository of formatted mathematical equations and guided examples for learning deep learning concepts. The project provides a mathematical reference for supervised learning and neural network theory using LaTeX rendering. It includes interactive technical documentation and executable notebooks covering gradients, convolutions, and transformers. The system manages educational materials through a file-system based organ
This repository is a collection of Jupyter notebooks teaching deep‑learning mathematics, not a self‑hostable platform with interactive problem sets, automated grading, or progress tracking; it provides LaTeX‑rendered examples for a narrow domain rather than a general mathematics learning tool.
This project is an educational resource focused on machine learning mathematics education. It provides a curriculum for the mathematical foundations required to understand and implement machine learning algorithms, covering linear algebra, calculus, probability, and optimization. The resource includes structured mathematics modules and a foundation curriculum paired with practice exercises, instructor manuals, and solution guides. It offers technical textbook supplementation through downloadable PDF materials and supplementary learning content such as video lectures and presentation slides.
This repository is a static textbook and curriculum site for machine-learning mathematics, not an interactive platform with automated grading, progress tracking, or self-hostable software features.
This project is an interactive machine learning textbook and educational resource designed to teach the mathematical foundations of artificial intelligence. It functions as a structured course and digital book that covers essential topics ranging from basic arithmetic to advanced calculus, linear algebra, and statistics. The resource utilizes a math visualization library and a collection of interactive code examples to demonstrate abstract principles through algorithmic output. It transforms theoretical study into a practical experience by combining programmable examples with visual guides.
This is an interactive notebook-based textbook on mathematics for machine learning, providing code examples and visualizations, but it is a static educational resource rather than a self-hostable platform with automated grading, progress tracking, or adaptive learning paths.
Rustlings is a command-line learning tool designed to build language proficiency through a structured, interactive curriculum. It functions as a practice-oriented platform where users master syntax and core concepts by resolving compilation errors within a sequence of small, incremental code exercises. The environment distinguishes itself by utilizing a compiler-driven feedback loop that parses error messages to provide targeted hints for fixing logic and syntax issues. Progress is managed through a file-based system where users modify incomplete source templates, which are then verified agai
Rustlings is an interactive, self-paced learning tool with exercises and automated feedback, but it teaches the Rust programming language rather than mathematics, so it doesn't match the mathematics-specific focus of this search.
Editor.md is an embeddable Markdown editor component for web applications that provides a real-time, dual-pane live preview alongside the raw source as the user types. It is designed as a plugin-based Markdown editor with a plugin architecture for extending functionality through custom modules, and it supports rendering LaTeX mathematical expressions using KaTeX as well as converting flowchart and sequence diagram syntax into visual diagrams within the preview. The editor distinguishes itself through its plugin-based extension system, which allows loading additional functionality through exte
Editor.md is an embeddable Markdown editor with LaTeX support, not an interactive mathematics learning platform—it lacks the problem sets, automated grading, and progress tracking this search requires.
MakerSkillTree is an educational roadmap designer and interactive skill map visualizer. It provides a system for creating, exporting, and navigating structured learning paths through an SVG skill tree generator and a corresponding YAML learning path schema. The project features a drag-and-drop interface for designing custom skill trees and a bidirectional conversion system that translates visual layouts between SVG and YAML formats. This allows for data-driven version tracking and the generation of changelogs between different iterations of a skill tree. The system supports the visualization
MakerSkillTree is a generic skill-tree and roadmap designer, not an interactive mathematics learning platform—it lacks the problem sets, automated grading, and LaTeX support your search requires, though it could help structure a math curriculum.
Beautiful and accessible math in all browsers
MathJax is a math rendering engine for displaying LaTeX and other math notations in browsers, not an interactive learning platform with problem sets, grading, or progress tracking—it's a useful component but not the self-hostable teaching tool this search targets.
handcalcs is a mathematical documentation generator and Python LaTeX calculation renderer. It serves as an automated calculation sheet tool that converts Python code and numeric calculations into formatted LaTeX mathematical documentation, functioning as both a symbolic math formatter and a Jupyter notebook math extension. The project transforms Python variable names into Greek symbols, subscripts, and standard mathematical notation. It converts code into formatted mathematical expressions that display the original formula, the numeric substitution, and the final result, allowing for the crea
handcalcs is a tool for rendering Python calculations into formatted LaTeX documentation, not an interactive mathematics learning platform with problem sets, grading, or progress tracking—it could serve as a LaTeX rendering component in such a platform, but is not itself the tool you're looking for.
This project is a web-native presentation framework that renders slide decks from standard HTML or Markdown. It functions as a declarative slide engine, managing navigation, state persistence, and lifecycle events through a configuration-driven interface. By leveraging standard web technologies, it enables the creation of responsive, browser-based presentations that support complex layouts, nested transitions, and interactive content. The framework distinguishes itself through a modular, plugin-based architecture that allows developers to extend core functionality using custom hooks and event
Reveal.js is a web-based presentation framework for slide decks, not an interactive mathematics learning platform with problem sets, grading, or progress tracking; while it supports LaTeX rendering and can be self-hosted, it lacks the core interactive learning features you need.
Streamdown is a streaming markdown renderer for React that transforms incoming markdown text into sanitized HTML in real time, handling incomplete blocks as they arrive. It parses GitHub-Flavored Markdown syntax including tables, task lists, and footnotes, and renders LaTeX math expressions using KaTeX, Mermaid diagrams as interactive SVGs, and code blocks with Shiki-based syntax highlighting supporting over 200 languages with dual light and dark themes. The renderer includes an XSS-safe HTML sanitizer that strips dangerous tags and validates URLs to prevent injection attacks. What distinguis
Streamdown is a React markdown renderer with LaTeX support, but it is not an interactive mathematics learning platform—it lacks problem sets, grading, and progress tracking, and is a component rather than a self-hostable application.
| Repository | Stars | Language | License | Last push |
|---|---|---|---|---|
| jushbjj/mr.-ranedeer-ai-tutor | 29.6K | — | — | |
| google/latexify_py | 7.6K | Python | Apache-2.0 | |
| shuhuai007/machine-learning-session | 5.2K | — | — | |
| katex/katex | 20.2K | TypeScript | MIT | |
| udlbook/udlbook | 9.1K | Jupyter Notebook | other | |
| mml-book/mml-book.github.io | 15.7K | Jupyter Notebook | — | |
| visualize-ml/book3_elements-of-mathematics | 7.5K | Jupyter Notebook | — | |
| rust-lang/rustlings | 63.3K | Rust | MIT | |
| pandao/editor.md | 14.3K | JavaScript | MIT | |
| sjpiper145/makerskilltree | 3.3K | Jinja | — |