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Batch Normalization - Is batch normalization better than dropout?
Answer
Batch normalization stabilizes the training process by lowering the internal covariate shift, while dropout assists in preventing overfitting by decreasing co-adaptation. Deep learning models can benefit from a combination of the two approaches.