How to use Batch Normalization with Keras?

The inputs to individual layers in a neural network can be normalized to speed up training. This process, called Batch...

What is Batch Normalization for training neural networks?

Training neural networks is an art rather than a process with a fixed outcome. You don’t know whether you’ll end...

Thanks to modern deep learning frameworks like Keras, it’s very easy to use particular datasets – which are included in...

When you’re creating a neural network for classification, you’re likely trying to solve either a binary or a multiclass classification...

Visualizing the structure of your neural network is quite useful for publications, such as papers and blogs. Today, various tools...

Flatten-T Swish is a new (2018) activation function that attempts to find the best of both worlds between traditional ReLU...

Over the last few years, we’ve seen the rise of a wide range of activation functions – such as FTSwish....

Datasets are crucial to functional machine learning models. Having a good dataset available can be the difference between success or...

In a different blog post, we studied the concept of a Variational Autoencoder (or VAE) in detail. The models, which...

Autoencoders are special types of neural networks which learn to convert inputs into lower-dimensional form, after which they convert it...