 Automatic differentiation

Automatic differentiation (AD) is a computational technique used to evaluate the derivative of a function specified by a computer program. AD is particularly useful in various fields including machine learning, optimization, and scientific computing because it allows for efficient and accurate computation of derivatives, which is crucial for gradient-based optimization methods.