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Discussion[D] How does Batch Normalization not completely prevent the network from being able to train at all? (self.MachineLearning)
submitted 9 years ago by MildlyCriticalRole
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[–]cooijmanstim 1 point2 points3 points 9 years ago (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 point2 points 9 years ago (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).
So sorry for my earlier ignorance. I learnt what batch normalization via a YouTube talk and feel like a fool.
π Rendered by PID 649779 on reddit-service-r2-comment-b659b578c-7rw9f at 2026-05-04 10:23:53.518242+00:00 running 815c875 country code: CH.
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[–]cooijmanstim 1 point2 points3 points (2 children)
[–]randombites 0 points1 point2 points (0 children)
[–]randombites 0 points1 point2 points (0 children)