A loss function is a mathematical expression used to measure the difference between predicted values and actual values. It is used to optimize a model by minimizing the difference between the two. The goal of a loss function is to minimize the error of the model.
For example, the mean squared error (MSE) loss function is commonly used in regression problems. It measures the average of the squares of the errors, or deviations, between predicted values and actual values. The goal is to minimize the MSE so that the model is as accurate as possible.