The Unsupervised Learning Workshop

5. Autoencoders

Overview

In this chapter, we will look at autoencoders and their applications. We will see how autoencoders are used in dimensionality reduction and denoising. We will implement an artificial neural network and an autoencoder using the Keras framework. By the end of this chapter, you will be able to implement an autoencoder model using convolutional neural networks.

Introduction

We'll continue our discussion of dimensionality reduction techniques as we turn our attention to autoencoders. Autoencoders are a particularly interesting area of focus as they provide a means of using supervised learning based on artificial neural networks but in an unsupervised context. Being based on artificial neural networks, autoencoders are ...