Deep learning applications can be viewed as a more sophisticated deployment of basic neural networks that make heavy use of machine learning algorithms, are inspired by the human mind, can keep ...

In addition to pure deep neural networks (DNNs), sometimes people use hybrid vision models, which combine deep learning with classical machine learning algorithms that perform specific sub-tasks.

Machine-learning algorithms are responsible for the vast majority of the artificial intelligence advancements and applications you hear about. (For more background, check out our first flowchart ...

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

With all the excitement over neural networks and deep-learning techniques, it’s easy to imagine that the world of computer science consists of little else. Neural networks, after all, have begun ...

However, it is more than that, which makes deep learning far better than any of the classical machine learning algorithms. Deep learning: Neural networks and functions.

Open source deep learning neural networks are coming of age. There are several frameworks that are providing advanced machine learning and artificial intelligence (A.I.) capabilities over ...

Geoffrey Hinton, professor at the University of Toronto and engineering fellow at Google Brain, recently published a paper on the Forward-Forward algorithm (FF), a technique for training neural networ ...

Born in the 1950s, the concept of an artificial neural network has progressed considerably. Today, known as “deep learning”, its uses have expanded to many areas, including finance.