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# Why does relu train faster than sigmoid?

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Efficiency: ReLu is faster to compute than the sigmoid function, and its derivative is faster to compute. This makes a significant difference to training and inference time for neural networks: only a constant factor, but constants can matter.

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SITHU Nyein does it also have to do with the fact that relu has less noise (deactivates neurons below zero completely, unlike sigmoid)?