Data is central to machine learning and AI. Tasks like recognition, decision-making and prediction require knowledge, which can only be learned through training. Just as a parent teaches their child ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

Researchers have determined how to build reliable machine learning models that can understand complex equations in real-world situations while using far less training data than is normally expected.

A research team of mathematicians and computer scientists has used machine learning to reveal new mathematical structure within the theory of finite groups. By training neural networks to recognise ...

Developers frequently turn to autoencoders to organize data for machine learning algorithms to improve the efficiency and accuracy of algorithms with less effort from data scientists. Data scientists ...

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 ...

Microsoft’s recent Azure Open Source Day showed off a new reference application built using cloud-native tools and services, with a focus on Microsoft’s own open source tools. The app was built to be ...