Batch normalization is a widely used technique for making neural-network training faster and more stable. It normalizes intermediate activations and then applies learned scale and shift parameters, allowing the model to keep the representation it needs. Normalization inside the network During training, batch normalization calculates a mean and variance from the current mini-batch. Activations are…
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