November 2017
Beginner to intermediate
366 pages
7h 59m
English
Softmax activation is most frequently used for classification tasks. Softmax rescales the output from the previous layer. First, it calculates the exponential of the input to its neuron and then it divides the total sum of input with all of the neurons in the layer, so that the activation sums up to one and lies between zero and one.
The softmax equation looks like this:
Softmax activation is used as the last layer in a deep learning neural network for multi-class classification. The layer has the same number of nodes as the number of classes and it rescales the output so that it adds up to 1.0, therefore calculating the ...
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