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 ...

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 ...

Zehra Cataltepe is the CEO of TAZI.AI an adaptive, explainable Machine Learning platform. She has more than 100 papers and patents on ML. While many believe that growth comes from acquiring new ...

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, ...

Machine learning might be the world’s most important general-purpose technology, but it’s notoriously difficult to launch. Outside of Big Tech and a handful of other leading companies, machine ...

In an X-note, Awni Hannun, of Apple’s ML team, calls the software: “…an efficient machine learning framework specifically designed for Apple silicon (i.e. your laptop!)” The idea is that it ...