Today, I’ve teamed up with Ram Cherukuri of MathWorks to provide an overview of the MathWorks toolchain for machine learning (ML) and the deployment of embedded ML inference on Arm Cortex-A using the ...

Qing Wei and colleagues from the College of Engineering, China Agricultural University, systematically elaborated on the ...

A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

If you’ve spent any time reading about artificial intelligence, you’ll almost certainly have heard about artificial neural networks. But what exactly is one? Rather than enrolling in a comprehensive ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the annual income of a person based on their sex, age, state where they live and ...

A deep neural network (DNN) is a system that is designed similar to our current understanding of biological neural networks in the brain. DNNs are finding use in many applications, advancing at a fast ...

The researchers discovered that this separation proves remarkably clean. In a preprint paper released in late October, they ...