Diff-zoo is a learning-focused handbook designed to demystify algorithmic differentiation (AD), the core technique powering modern machine learning frameworks. The project introduces AD from a foundational calculus perspective and gradually builds towards toy implementations that resemble systems like PyTorch and TensorFlow. It clarifies the differences and connections between forward mode, reverse mode, symbolic, numeric, tracing, and source transformation approaches to differentiation....