ReLU Activation Function

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neural-networks Google Meta OpenAI

Multiple Choice

ReLU outputs values between 0 and 1, making it easier to interpret ReLU mitigates the vanishing gradient problem and is computationally cheaper to evaluate ReLU always produces non-zero gradients, ensuring all neurons learn ReLU is differentiable everywhere, unlike sigmoid

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