The importance of loss function in artificial intelligence

Abstract

As known, Artificial Intelligence is based on Machine Learning(ML) and Deep Learning(DL). And improving ML and DL is connected to Loss function in neural networks. In the importance optimization algorithms Loss function of great importance. There are different types of Loss function in Artificial Intelligence. In this article, some Loss types are illustrated advantages (disadvantages) and analyzed with examples. We may seek to maximize or minimize the objective function, meaning that we are searching for a candidate solution that has the highest or lowest score respectively. Typically, with neural networks that are one of the main part of the Artificial intelligence, we seek to minimize the error. As such, the objective function is often referred to as a cost function or a loss function and the value calculated by the loss function is referred to as simply “Loss.”