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Softmax Function is a easy coding interview question covering math, deep learning — the kind asked at FAANG (Facebook/Meta, Apple, Amazon, Netflix, Google) and AI-first companies like Anthropic, OpenAI, and Nvidia.
Implement the softmax function used in the output layer of multi-class classification models to produce a probability distribution.
softmax(x_i) = e^(x_i) / sum(e^(x_j) for all j)
For numerical stability, subtract max(x) before exponentiating.
Example: [1.0, 2.0, 3.0] -> approximately [0.090, 0.245, 0.665]
All outputs sum to 1.0. Used in every classification neural network.
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