Your question is Batch Normalization Basics. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
What is batch normalization?
Explain the normalization operation, the learnable scale and shift parameters, and how batch statistics differ between training and inference. Describe where batch normalization is typically placed in a neural network, its effect on optimization, and important limitations such as small batch sizes and distribution differences between training and serving. Include a short implementation or pseudocode example and explain how you would evaluate whether it improves training.
