Explainer: the softmax function and its derivative
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Softmax maps an N-dimensional vector of arbitrary reals to values in (0,1) that sum to 1.0, e.g. [1.0, 2.0, 3.0] becomes [0.09, 0.24, 0.67]. The probabilistic interpretation underlies multiclass logistic regression, where a weight matrix W is applied to input x before softmax.
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