Using denoising autoencoders to detect fraudulent transactions

In Chapter 4, Clustering with Unsupervised Learning, we dealt with the topic of autoencoders. In the Autoencoders to reconstruct handwritten digit images recipe, there is a neural network whose purpose is to code its input into small dimensions, and the result obtained, to be able to reconstruct the input itself. The purpose of autoencoders is not simply to perform a sort of compression of the input or look for an approximation of the identity function; there are also techniques that allow us to direct the model (starting from a hidden layer of reduced dimensions) to give greater importance to some data properties.

Getting ready

In this recipe, we will train an...