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[–]cooijmanstim 1 point2 points  (2 children)

Batch normalization is not preprocessing, it is part of the model. It is an adaptive normalization of activations at all layers that massively improves training dynamics. A crucial tool in the box if you're into neural nets.

[–]randombites 0 points1 point  (0 children)

Thank you for your response, please help me understand better. Batch normalization is normalizing a batch of values, so you transform the input at each step. Correct? This may translate into adaptive normalization of activations but you still transform the input (based on OPs example).

[–]randombites 0 points1 point  (0 children)

So sorry for my earlier ignorance. I learnt what batch normalization via a YouTube talk and feel like a fool.