Visual Studio Magazine

Regression Using a scikit MLPRegressor Neural Network

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 ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Visual Studio Magazine

Neural Regression Using PyTorch: Defining a Network

Dr. James McCaffrey of Microsoft Research presents the second of four machine learning articles that detail a complete end-to-end production-quality example of neural regression using PyTorch. The ...
Semiconductor Engineering

Deep Learning Neural Networks Drive Demands On Memory Bandwidth

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 ...
Science Daily

Adaptive optical neural network connects thousands of artificial neurons

Modern computer models -- for example for complex, potent AI applications -- push traditional digital computer processes to their limits. New types of computing architecture, which emulate the working ...
InfoWorld

Styles of machine learning: Intro to neural networks

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks. Artificial intelligence ...
The Next Web

Deep learning models DON’T need to be black boxes — here’s how

Deep neural networks can perform wonderful feats thanks to their extremely large and complicated web of parameters. But their complexity is also their curse: The inner workings of neural networks are ...