Final answer:
Gradient Descent (GD) is a mathematical optimization algorithm used to find the bottom or optimum of a function.
Step-by-step explanation:
In mathematics, Gradient Descent (GD) is a popular optimization algorithm used to find the bottom or optimum of a function.
GD works by iteratively adjusting the parameters of a function to minimize its value. The direction and step size of each adjustment are determined by the gradient (partial derivatives) of the function.
To get to the bottom/optimum with GD, you start with an initial set of parameters, calculate the gradient, and update the parameters according to a learning rate. This process is repeated until the function reaches a minimum or converges to a specific value.