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...

Making more datasets available for Keras

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...

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...

Suppose that you have an image of a man with a moustache and one of a man without one. You...

When you train a supervised machine learning model, you feed forward data, generating predictions on the fly. The comparison of...

Pure signals only exist in theory. That is, when you’re doing signal processing related activities, it’s very likely that you’ll...