This article explains how to use a PyTorch neural autoencoder to find anomalies in a dataset. A good way to see where this article is headed is to take a look at the screenshot of a demo program in ...

The computed output is (0.00390, 0.39768, -0.00035, -0.00252, 1.00286, 0.50118, -0.00225, 1.00290, -0.00065) which is reasonable, as will be explained shortly. The trained neural autoencoder model is ...