Gradient Descent is a first-request iterative improvement calculation for finding a nearby least of a differentiable capacity. To locate a neighborhood least of a capacity utilizing Gradient Descent, we make strides corresponding to the negative of the inclination (or surmised slope) of the capacity at the current point.

Learning Rate controls the magnitude of a step taken during Gradient Descent .