Automatic Differentiation

Automatic differentiation is a set of techniques used to numerically evaluate the derivative of a function specified by a computer program, allowing for efficient and accurate computation of gradients in various fields such as machine learning and scientific computing. By automating the process of differentiation, it enables developers to optimize complex models and algorithms, making it a crucial tool for applications like deep learning, optimization, and sensitivity analysis.