Maths, CS & AI Compendium is an open-source educational textbook covering mathematics, computer science, and artificial intelligence with emphasis on intuition and practical understanding.
The project addresses the gap between traditional dense textbooks and the needs of practitioners entering AI and machine learning fields. Rather than burying concepts under notation or skipping foundational intuition, it builds understanding from the ground up with real-world context and clear explanations. The material originated from personal notes accumulated during professional work in AI and ML, refined through use by others preparing for technical interviews and roles at major AI organizations.
The tool suits developers and researchers who want to deeply understand AI and ML fundamentals rather than memorize for exams. It works best for those entering the field or seeking to fill gaps in their mathematical and computational foundations. The compendium covers linear algebra, probability, statistics, algorithms, deep learning, computer vision, natural language processing, reinforcement learning, and multimodal learning, with implementations using frameworks like JAX.
The project includes an MCP server integration that allows AI assistants such as Claude Code, Cursor, and VS Code to access the compendium as a knowledge base when the repository is cloned locally, enabling interactive learning and reference during development work. Development activity shows consistent engagement with the material, with updates reflecting both the evolving landscape of AI research and feedback from users applying the content to real technical challenges.
