Latent space visualization -- Deep Learning bits #2 – Julien Despois – Medium

Last time, we have seen what autoencoders are, and how they work. Today, we will see how they can help us visualize the data in some very cool ways. For that, we will work on images, using the Convolutional Autoencoder architecture (CAE). An autoencoder is made of two components, here's a quick reminder. The encoder brings the data from a high dimensional input to a bottleneck layer, where the number of neurons is the smallest.