This repository provides an educational resource explaining ML concepts from first principles, using engineering analogies to build intuition. It covers fundamentals like neurons, backpropagation, generalization, and representation, then progresses to architectures including transformers, convolutions, and recurrence. The material is organized as a mental model guide rather than a typical textbook or tutorial.