Neural network dropout is a technique that can be used during training. It is designed to reduce the likelihood of model overfitting. You can think of a neural network as a complex math equation that ...

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 ...

Around the Hackaday secret bunker, we’ve been talking quite a bit about machine learning and neural networks. There’s been a lot of renewed interest in the topic recently because of the success of ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

Neural networks usually run on electronics, but Caltech researchers are pushing boundaries by building networks out of DNA molecules . Instead of using digital signals, these molecular systems compute ...