Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech researchers have been developing a neural network made out of strands of DNA instead ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Machine learning with neural networks is sometimes said to be part art and part science. Dr. James McCaffrey of Microsoft Research teaches both with a full-code, step-by-step tutorial. A binary ...

Graph Neural Networks (GNN), a cutting-edge approach in artificial intelligence, can significantly improve computational calculations in heterogeneous catalysis. Researchers have made a groundbreaking ...

A new study shows that the physics principle of 'nucleation' can perform complex calculations that rival a simple neural network. The work may suggest avenues for new ways to think about computation ...

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 binary classification problem is one where the goal is to predict the value of a variable where there are exactly two discrete possibilities. For example, you might want to predict the sex of a ...