Question: The softmax function normalizes a vector so its entries are positive and sum to . This is useful for creating a probability distribution across the

The softmax function normalizes a vector so its entries are positive and sum to
. This is useful for creating a probability distribution across the vector, so it is commonly used as the final activation layer for neural networks (especially since the gradient of the softmax function is relatively easy to compute).

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