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 ...

Autoencoder networks: the core of the attentional autoencoder network is the autoencoder. An autoencoder is a neural network structure that consists of an encoder and a decoder.

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...