Categorical Cross Entropy Loss - Deep Learning Dictionary
Categorical cross entropy - Deep Learning Dictionary
A loss function allows us to measure the error of the network during training. It gives us a measure of how well the network is learning the data. The smaller the loss, the better the network has learned the data.
Categorical cross entropy loss is the most common choice for loss functions used in neural network classification tasks. This loss function measures the difference between two probability distributions.
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