Create a fully connected feedforward neural network from the ground up with Python — unlock the power of deep learning!

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling ...

With Python and NumPy getting lots of exposure lately, I'll show how to use those tools to build a simple feed-forward neural network.

Understanding how neural networks work at a low level is a practical skill for networks with a single hidden layer and will enable you to use deep neural network libraries more effectively.

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks.

Deep learning's availability of large data and compute power makes it far better than any of the classical machine learning algorithms.

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.

The 2012 breakthrough—the deep learning revolution—was the discovery that we can get dramatically better performance out of neural networks with not just a few layers but with many.