How to Accelerate Learning of Deep Neural Networks With Batch Normalization

Batch normalization is a technique designed to automatically standardize the inputs to a layer in a deep learning neural network. Once implemented, batch normalization has the effect of dramatically accelerating the training process of a neural network, and in some cases improves the performance of the model via a modest regularization effect. In this tutorial, you will discover how to use batch normalization to accelerate the training of deep learning neural networks in Python with Keras. How to Accelerate Learning of Deep Neural Networks With Batch Normalization Photo by Angela and Andrew, some rights reserved. Keras provides support for batch normalization via the BatchNormalization layer.