We’ve gotten pretty good at building machine learning models. From legacy platforms like SAS to modern MPP databases and Hadoop clusters, if you want to train up regression or classification models, ...

In this special guest feature, Neil Cohen, Vice President at Edge Intelligence, examines the question: where should businesses develop and execute machine learning? This article explores the pros and ...

With so many machine learning projects failing to launch – never achieving model deployment – the ML team has got to do everything in their power to anticipate any impediments to model ...

Machine learning has moved past its initial experimental phase. In earlier years, development often focused on creating the largest possible models to see what capabilities might appear. Today, the ...

Linux has long been the backbone of modern computing, serving as the foundation for servers, cloud infrastructures, embedded systems, and supercomputers. As artificial intelligence (AI) and machine ...

z System users with data behind their firewalls can now access IBM's training and deployment system for machine learning, packaged for convenience If you’re intrigued by IBM’s Watson AI as a service, ...

The study, titled “Teach AI What It Doesn’t Know,” published in AI Magazine, presents a detailed research agenda by Sean Du of Nanyang Technological University, focused on building reliable machine ...

Transcripts are generated using a combination of speech recognition software and human transcribers, and may contain errors. Please check the corresponding audio for the authoritative record. Penny ...

The field of intelligent energy systems has witnessed a remarkable transformation owing to innovations in machine learning. Over the past few decades, the ...

Eric Siegel had already been working in the machine learning world for more than 30 years by the time the rest of the world caught up with him. Siegel’s been a machine learning (ML) consultant to ...