Deep learning models, such as neural networks, build abstract representations of data during the training phase. In this stage, the goal is to optimize a cost function—either by minimizing or maximizing it—using algorithms like those from the gradient descent family. In neural networks, this process is applied to each layer of the model. Thus, each…