The computation of the difference between the predicted and actual value using a function is known as the loss function. The value of this function defines the amount of difference in values.
Hence at each run, the Gradient Function optimizer checks for the changes which can help to improve the model. With the help of optimizer, the loss reduces to the minimum and attains maximum accuracy.
