Readers of this blog already know what loss functions are in AI but for people starting into the field let me define it again. The loss function is a mathematical equation that all the deep learning algorithm tries to minimize or optimize. As we all know that Deep learning takes an iterative process to learn things, in every step, it calculates some metric that tells it how close it is to the original label and based upon that it optimizes its parameters. So the metrics that we minimize or optimize are called loss functions. There are a lot of famous loss functions like Mean square error, categorical cross-entropy, Dice loss, and many more.
Nov-27-2021, 23:55:06 GMT