To extract more powerful and robust feature representations from the rating matrix, they proposed a serial autoencoder structure to improve the model recommendation performance.

The overall structure of the PyTorch autoencoder anomaly detection demo program, with a few minor edits to save space, is shown in Listing 3. I prefer to indent my Python programs using two spaces ...

Compared to using PCA for dimensionality reduction, using a neural autoencoder has the big advantage that it works with source data that contains both numeric and categorical data, while PCA works ...