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 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 ...

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 ...

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 ...

• UPS saves 10 million gallons of fuel and $50 million each year because of their algorithm-powered Orion (on-road integrated optimization and navigation) platform. With their dynamic parceling ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

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 ...