Summary

This repository offers an unconventional, open textbook designed to teach mathematics, computing, and artificial intelligence with a strong emphasis on intuition and real-world context. It targets curious practitioners seeking deep understanding beyond exam preparation, aiming to demystify complex topics often obscured by dense notation in traditional texts.

How It Works

The project presents a ground-up curriculum structured into chapters covering foundational mathematics (vectors, matrices, calculus, probability, statistics) and advanced AI/ML concepts (deep learning, NLP, computer vision, multimodal learning, autonomous systems). Its core approach prioritizes intuitive explanations and practical relevance, drawing from the author's experience in AI/ML research and development, making it accessible for self-study and skill enhancement.

Quick Start & Requirements

This is a textbook resource, not a software package. No installation or execution commands are applicable. The primary resource is the GitHub repository itself, which hosts the content. Further details and community interaction can be found via GitHub issues.

Highlighted Details

• Offers comprehensive coverage from foundational math to cutting-edge AI, including modern LLM architectures, transformers, diffusion models, and SIMD/GPU programming (CUDA, Triton).
• Content is derived from practical experience, including notes used for successful interview preparation at leading AI labs like DeepMind and OpenAI.
• Core foundational chapters (01-06) are currently available, with a roadmap indicating future additions across a wide range of advanced topics.
• Emphasizes intuition and avoids the dense notation and assumptions common in traditional academic texts.

Maintenance & Community

The project is maintained by Henry Ndubuaku, with contributions welcomed via GitHub issues for topic suggestions and pull requests for corrections and improved explanations. The repository serves as the central hub for content updates and community interaction.

Licensing & Compatibility

The license for this open textbook is not explicitly stated in the provided README. Potential users should verify licensing terms before integrating or referencing the content, especially for commercial applications.

Limitations & Caveats

A significant portion of the planned content, particularly in advanced AI subfields, computer vision, audio, autonomous systems, and systems design, is marked as "Coming" and not yet available. The absence of a specified license is a notable caveat for adoption.