Batch Normalization

Batch Normalization is an essential tool used in modern deep learning workflows.

Soon after it was introduced in the Batch Normalization paper, it completely changed the neural network space, as it helped create deeper neural networks that could be trained faster.

Batch Normalization is a neural network layer that is commonly used in many architectures.

• It often gets added as part of a Fully-Connected or Convolutional block and helps stabilize the network during training.