Numerical Analysis Questions
Unconstrained optimization in Numerical Analysis refers to the process of finding the minimum or maximum value of a function without any constraints or limitations on the variables. It involves finding the optimal solution within a given domain by iteratively adjusting the variables to minimize or maximize the objective function. Various numerical methods, such as gradient descent, Newton's method, and the simplex method, are used to solve unconstrained optimization problems.