James McCaffrey uses cross entropy error via Python to train a neural network model for predicting a species of iris flower. In this article, I explain cross entropy ...

Regularization is a technique used to reduce the likelihood of neural network model overfitting. Model overfitting can occur when you train a neural network for too many iterations. This sometimes ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

Neural networks have enjoyed several waves of popularity over the past half century. Each time they become popular, they promise to provide a general purpose artificial intelligence–a computer that ...

Unlock access to every one of the hundreds of articles published daily on BroadwayWorld by logging in with one click. CAMBRIDGE, MA - Elsevier, the information analytics company specializing in ...

There are many stories of how artificial intelligence came to take over the world, but one of the most important developments is the emergence in 2012 of AlexNet, a neural network that, for the first ...

Two new approaches allow deep neural networks to solve entire families of partial differential equations, making it easier to model complicated systems and to do so orders of magnitude faster. In high ...