Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed by University of Michigan researchers to train a material.

Gradient descent (GD) is a basic optimization technique ... Specifically, it forms the backbone for training these complex ...

This material, notably the backpropagation algorithm ... We will start with Stochastic Gradient Descent (SGD). SGD has several design parameters that we can tweak, including learning rate, momentum, ...