A diagram from the patent depicting a system for quantitative measurement of texture attributes. Artificial intelligence—and its machine learning applications in particular—have been attracting the ...

Machine-learning algorithms find and apply patterns in data. And they pretty much run the world. Machine-learning algorithms are responsible for the vast majority of the artificial intelligence ...

A year and a half ago, I wrote that robotic process automation might not be smart enough to fuel your digital transformation. But I needn’t have worried; RPA vendors are increasingly combining the ...

Automated machine learning (autoML) is the process of applying tools to data to apply the machine learning process to a real-world problem. Applying machine learning to a new dataset is a complicated ...

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 ...

Human-in-the-loop machine learning takes advantage of human feedback to eliminate errors in training data and improve the accuracy of models. Machine learning models are often far from perfect. When ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...