Explain the advantages and disadvantages of using Newton’s method versus a first-order method like SGD for optimizing the neural network’s loss function, including any specific considerations for your team’s use case.

Newton’s method can provide faster convergence to optimal solutions but requires access to the Hessian matrix of the loss function. In contrast, first-order methods like SGD are typically faster and easier to implement but may converge slowly to suboptimal solutions.