Gradient descent is an iterative optimization algorithm that is used for finding the local/global minimum of a differential function. Since the main goal of this function is to find the minimum, it is widely used in machine learning to find the perfect parameters that minimize the cost value.

In this article, we will see how this algorithm works, the mathematics behind this algorithm, and the types of gradient descent.

How Exactly is it used in machine learning?