Show HN: Maths, CS and AI Compendium (github.com)

A new open-source textbook titled "Maths, CS & AI Compendium" has been announced by Henry Ndubuaku, aiming to bridge the gap between complex theory and intuitive understanding in mathematics, computer science, and artificial intelligence. After seven years of gathering notes that prioritize real-world context and clear explanations over dense notation, Ndubuaku's resource provides a structured learning path designed for practitioners looking to deepen their knowledge rather than merely preparing for exams. The compendium is set to be continuously updated, starting with foundational topics such as vectors, matrices, calculus, and statistics, and progressing to advanced areas like machine learning, computer vision, and autonomous systems. This initiative is significant for the AI/ML community as it responds to the limitations of conventional textbooks, particularly in fast-evolving fields like AI. By focusing on practical applications and a clear understanding of theoretical concepts, this compendium can enhance the educational resources available to aspiring AI practitioners and researchers. Key topics include classical machine learning techniques, deep learning architectures, and a variety of interdisciplinary applications, such as quantum ML and multimodal learning, ensuring a comprehensive coverage that aligns with modern industry demands. The project encourages collaboration through suggestions and corrections via GitHub, aiming for a community-driven evolution of the material.