ML//neural network//loss function//cross-entropy

- Standard loss for classification: -log(p) where p is the predicted probability of the correct class.

Standard loss for classification: -log(p) where p is the predicted probability of the correct class.

Wrong and confident = massive penalty. Right and confident = tiny loss.