In this chapter, we learned that autoencoders are a technique used mainly in image reconstruction and denoising, to obtain compressed and summarized representations of the data. We saw that they are also used sometimes for fraud detection tasks. The outlier identification comes from measuring the reconstruction error, observing the distribution of the reconstruction error, we can set up thresholds for identifying the outliers and learn the probabilistic process that generates the data. Hence, Variational Autoencoders are also able to generate new data.