How Does Batch Normalization In Deep Learning Work?
Pickl AI
NOVEMBER 13, 2024
Summary: Batch Normalization in Deep Learning improves training stability, reduces sensitivity to hyperparameters, and speeds up convergence by normalising layer inputs. However, training deep neural networks often encounters challenges such as slow convergence, vanishing gradients, and sensitivity to initialisation.
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