Steepest Descent Method: A Gradient-Based Optimization Algorithm for N-Dimensional Function Minimization

The Steepest Descent Method is an optimization technique that searches for the minimum of an N-dimensional objective function by following the negative gradient direction. This program implements the method to solve unconstrained optimization problems with step size control and convergence criteria.