Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even ...

Marine cone snails are host to a family of dangerous neurotoxins. Very little is known about how those toxins interact with ...

But that’s all par for the course in AI and machine learning. If you’re looking to take a step up from here, we’d recommend this robot that uses neural networks to learn how to walk.

The most useful applications, though, require access to a remote server to do the heavy computational lifting of neural network code, and that severely limits the ways in which that code can be used.

It focuses on the use of ML, particularly neural networks (NNs), for simulating and forecasting the state of health (SOH) of lithium-ion batteries.

A subset of machine learning, neural networks are inspired by the simple animal brain mechanism of neurons and synapses -- inputs and outputs, Townsend said.

Keras, a Python-based deep learning library, was developed to enable fast experimentation and ease of use for building and training deep neural networks. It works as an interface for the machine ...

Fortunately, neural networks eat big, complicated data sets for breakfast. Google has been working on a machine learning translation technique for years, and today is its official debut.

Graph neural networks (GNN) are a type of machine learning algorithm that can extract important information from graphs and make useful predictions. With graphs becoming more pervasive and richer ...