A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

The race is on to create one neural network that can process multiple kinds of data -- a more-general artificial intelligence that doesn't discriminate about types of data but instead can crunch them ...

Dr. Tam Nguyen receives funding from National Science Foundation. He works for University of Dayton. There are many applications of neural networks. One common example is your smartphone camera’s ...

Training a neural network involves feeding it enough raw data to start recognizing and replicating patterns. It can be a long, tedious process to just approximate complex things -- like writing ...

If you’ve spent any time reading about artificial intelligence, you’ll almost certainly have heard about artificial neural networks. But what exactly is one? Rather than enrolling in a comprehensive ...

Neural networks have a reputation for being computationally expensive. But only the training portion of things really stresses most computer hardware, since it involves regular evaluations of ...

The best way to understand neural networks is to build one for yourself. Let's get started with creating and training a neural network in Java. Artificial neural networks are a form of deep learning ...

The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...