BatchNormalization is a layer in the TensorFlow library's Keras API. It is used to normalize the activations of a neural network's input across a given mini-batch. This normalization helps to stabilize and speed up the training process by reducing the internal covariate shift. It achieves this by normalizing the output using the mean and variance of the current batch, and then scaling and shifting the normalized output using learnable parameters. Overall, BatchNormalization aids in improving the convergence and generalization performance of neural networks.
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