Deep Learning - Convolutional Neural Networks with TensorFlow - Batch Normalization

The video tutorial explains batch normalization, a technique used in training neural networks to ensure data is normalized at every layer. It describes the process of batch normalization, which involves normalizing data using batch statistics and then rescaling and reshifting it for optimal performance. The tutorial also highlights batch normalization's role as a regularizer by introducing noise, making the network robust to variations. Finally, it discusses the application of batch normalization in convolutional neural networks (CNNs) and provides guidance on its implementation.

In what context is batch normalization mostly used?

Describe a common pattern for applying batch normalization in a convolutional neural network.

What is the significance of the paper titled 'Batch normalization: Accelerating deep network training by reducing internal covariate shift'?