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Layer Normalization Forward Pass is a easy coding interview question covering deep learning, math — the kind asked at FAANG (Facebook/Meta, Apple, Amazon, Netflix, Google) and AI-first companies like Anthropic, OpenAI, and Nvidia.
Implement the layer normalization forward pass used in every transformer block: normalize a vector to zero mean and unit variance over its own features (with epsilon for stability), then apply learned scale (gamma) and shift (beta) parameters.
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