Loss Functions Explained

In any deep learning project, configuring the loss function is one of the most important steps to ensure the model will work in the intended manner. The loss function can give a lot of practical flexibility to your neural networks and it will define how exactly the output of the network is connected with the rest of the network. There are several tasks neural networks can perform, from predicting continuous values like monthly expenditure to classifying discrete classes like cats and dogs. Each different task would require a different type of loss since the output format will be different. For very specialized tasks, it's up to us how we want to define the loss.