Neural Networks, Gradient Descent.
minima as the function is convex at x. For our example function f′′(x)= d²y/dx² = 2, indicating it is a convex function which means x=0 is the minimum and putting this value of x in the original function gives y=-16 as the minimum of the function If you do not know calculus and do not understand