Role of Choosing Correct Loss Function

Loss functions play a very important role in the training of modern Deep learning architecture, choosing the right loss function is the key to successful model building. A loss function is a mathematical equation that a deep learning architecture tries to minimize or optimize. Deep learning is an iterative process, in every step, it calculates some metric that tells the system how close its prediction is to the original label. Based on the calculated loss value, the network optimizes its parameters. There are a lot of loss functions and among those, the most popular ones are Mean square error, categorical cross-entropy, Dice loss, etc. Loss functions can be divided into two major categories: specialized loss functions and generalized loss functions.