A Novel Way to Use Batch Normalization

Batch normalization is essential for every modern deep learning algorithm. Normalizing output features before passing them on to the next layer stabilizes the training of large neural networks. Of…

An Alternative To Batch Normalization

The development of Batch Normalization(BN) as a normalization technique was a turning point in the development of deep learning models, it enabled various networks to train and converge. Despite its…

Batch Normalization

The idea is that, instead of just normalizing the inputs to the network, we normalize the inputs to layers within the network. It’s called “batch” normalization because during training, we normalize…

Batch Normalization

Training deep neural networks is difficult. Getting them to converge in a reasonable amount of time can be tricky. In this section, we describe batch normalization , a popular and effective technique ...

Batch normalization in 3 levels of understanding

There is a lot of content about Batch Normalization (BN) on the internet. Yet, many of them are defending an outdated intuition about it. I spent a lot of time putting all this scattered information…

Cross-iteration batch normalization

3. But we don’t always want hidden units to have mean 0 and SD 1, but in practice, we let the units have different distribution by introducing gamma and beta. In BN, it is assumed that the…

Batch Normalisation Explained

A simple, in-depth explanation of how batch normalisation works, and the issues it addresses.

Batch Normalization — an intuitive explanation

How Batch Normalization (BN) helps train better deep learning models

Speeding Up Training of Neural Networks with Batch-Normalization

One of the most essential Key-Techniques in Deep Learning Continue reading on Towards Data Science

Deep learning basics — batch normalization

Batch normalization normalizes the activations of the network between layers in batches so that the batches have a mean of 0 and a variance of 1. The batch normalization is normally written as…

Curse of Batch Normalization

Batch Normalization is Indeed one of the major breakthrough in the field of Deep Learning and is one of the hot topics for discussion among researchers in the past few years. Batch Normalization is a…...

Batch Normalization In Neural Networks (Code)

And if you haven’t, this article explains the basic intuition behind BN, including its origin and how it can be implemented within a neural network using TensorFlow and Keras. For those who are…

Implementing Batch Normalization in Python

Batch normalization deals with the problem of poorly initialization of neural networks. It can be interpreted as doing preprocessing at every layer of the network. It forces the activations in a netwo...

Latest picks: Batch normalization in 3 levels of understanding

Exploring Batch Normalisation with PyTorch

In continuation of my previous post, in this post we will discuss about “Batch Normalisation” and its implementation in PyTorch. Batch normalisation is a mechanism that is used to improve efficiency…

Batch normalization: theory and how to use it with Tensorflow

Not so long ago, deep neural networks were really difficult to train, and making complex models converge in a reasonable amount of time would have been impossible. Nowadays, we have a lot of tricks…

[ CVPR 2018 / Paper Summary ] Decorrelated Batch Normalization

There are multiple of different version of normalization such as instance normalization or group normalization. This is a new approach in which the layer performs statistical whitening on the given…

Batch Normalization in practice: an example with Keras and TensorFlow 2.0

In this article, we will focus on adding and customizing batch normalization in our machine learning model and look at an example of how we do this in practice with Keras and TensorFlow 2.0. In the…

Visualizing What Batch Normalization Is and Its Advantages

Introduction Have you, when conducting deep learning projects, ever encountered a situation where the more layers your neural network has, the slower the training becomes? If your answer is YES, then ...

What is batch normalization?

Batch normalization was introduced by Sergey Ioffe’s and Christian Szegedy’s 2015 paper Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. Batch…

Batch Normalization: A different perspective from Quantized Inference Model

The benefits of Batch Normalization in training are well known for the reduction of internal covariate shift and hence optimizing the training to converge faster. This article tries to bring in a…

Understanding Batch Normalization for Neural Networks

One of the main assumptions made when training learning systems is to suppose that the distribution of the inputs stays the same throughout the training. For linear models, which simply map input…

Batch Normalization, Instance Normalization, Layer Normalization: Structural Nuances

This short post highlights the structural nuances between popular normalization techniques employed while training deep neural networks. Let us establish some notations, that will make the rest of…

Why Batch Normalization Matters?

Batch Normalization(BN) has become the-state-of-the-art right from its inception. It enables us to opt for higher learning rates and use sigmoid activation functions even for Deep Neural Networks. It…...