Automatic differentiation

Automatic differentiation is a computational technique used to calculate the derivatives of functions efficiently and accurately. It operates by breaking down complex calculations into simpler parts, applying the rules of calculus automatically. This is especially valuable in fields like machine learning, where understanding how changes in inputs affect outputs is crucial for optimizing models. Unlike numerical differentiation, which estimates derivatives and can introduce errors, automatic differentiation produces exact derivatives, making it a powerful tool in scientific computing and optimization tasks.