Portfolio Details

Description

This project developed a package designed to calculate the first-order derivatives of user-defined functions using both forward and reverse modes of automatic differentiation. Unlike symbolic or numerical differentiation, automatic differentiation offers a more efficient and precise way to compute derivatives, making it particularly useful in fields like machine learning, data science, and signal processing.