Batch Norm Explained Visually -- How it works, and why neural networks need it

Batch Norm is an essential part of the toolkit of the modern deep learning practitioner. Soon after it was introduced in the Batch Normalization paper, it was recognized as being transformational in creating deeper neural networks that could be trained faster. Batch Norm is a neural network layer that is now commonly used in many architectures. It often gets added as part of a Linear or Convolutional block and helps to stabilize the network during training. In this article, we will explore what Batch Norm is, why we need it and how it works.