What does function loss mean?

Function loss, often referred to as loss or cost function, measures the difference between the predicted values of a model and the actual target values during training. It quantifies how well the model is performing; a lower loss indicates better performance. The objective of training a machine learning model is to minimize this loss, thereby improving the model's accuracy and generalization on unseen data. Different types of loss functions exist, tailored to specific tasks such as regression or classification.