Gradient descent

Gradient Descent is a method used to find the minimum of a function. Imagine walking downhill towards the lowest point in a valley—that's what this method does mathematically. It calculates the gradient (the slope) of the function and takes steps in the direction that decreases the function's value. It's powerful for optimizing in machine learning and economics. However, it struggles with functions having many valleys (local minima) or plateaus, and might not find the absolute lowest point (global minimum).