A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

While neural networks (also called “perceptrons”) have been around since the 1940s, it is only in the last several decades where they have become a major part of artificial intelligence.

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

The demo program creates and trains a 784-100-50-100-784 deep neural autoencoder using the Keras library. An autoencoder is a neural network that learns to predict its input. After training, the demo ...

Implementing a deep autoencoder is possible but requires a lot of effort. A result from the Universal Approximation Theorem (sometimes called the Cybenko Theorem) states, loosely speaking, that a ...