Loss function
Similar to other machine learning models, a neural network has a loss function.
This is a function which computes how accurate the model is. Large loss values indicate poor “accuracy” (and vice-versa) and so we try to minimise the outcome of the loss function.
If we think of model error as a “cost”, then we can think of a loss function as a cost function and the idea of minimising loss is more intuitive.