Deep neural networks are at the heart of artificial intelligence, ranging from pattern recognition to large language and ...

Our data science expert continues his exploration of neural network programming, explaining how regularization addresses the problem of model overfitting, caused by network overtraining.

Researchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural networks (RNNs) that ...

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

Researchers at DeepMind claim that neural networks can outperform models with hardcoded rules and symbolic knowledge.

A team of environmental and computation scientists is using deep neural networks, a type of machine learning, to replace the parameterizations of certain physical schemes in the Weather Research ...

Artificial neural networks are viable models for a wide variety of problems, including pattern classification, speech synthesis and recognition, adaptive interfaces between humans and complex ...

The data science doctor continues his exploration of techniques used to reduce the likelihood of model overfitting, caused by training a neural network for too many iterations.