What is ‘batch normalization’ and why is it used in deep neural networks?

Question

AI Fundamentals — Medium

What is ‘batch normalization’ and why is it used in deep neural networks?

Accepted Answer

Batch normalization is a technique that normalizes layer inputs across a mini-batch, stabilizing training, speeding up convergence, and acting as regularization. It helps in maintaining consistent activations throughout the network, leading to faster and more stable training.