automatic differentiation in deep learning nowcoming to our end objectiveto find the gradients of with regard to xy and we already have computed the required gradient with regard to for and ywe can leverage the previously computed values in chain rule as we now have computed all the values required - and essentiallywhat network would infer is that and positively influence the outcomewhereas negatively influences it (figure - this information is useful to reduce the loss and updates the weights of the network incrementally to reach the minima figure - computational graph with partial derivatives