Can you explain the concept of batch normalization in neural networks? Describe its purpose, how it works, and discuss its impact on the training process and the performance of deep learning models. Additionally, highlight any potential drawbacks or scenarios where batch normalization might not be as effective.

Batch Normalization is a technique used in deep neural networks to improve training speed, stability, and convergence. Its primary purpose is to address the issue of internal covariate shift, which refers to the **change in the distribution...