Changing assumptions and ever-changing data mean the work doesn’t end after deploying machine learning models to production. These best practices keep complex models reliable. Agile development ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

Whereas a rule-based system will perform a task the same way every time (for better or worse), the performance ... machine learning algorithms for regression and classification. A clustering ...

Teaching AI to explore its surroundings is a bit like teaching a robot to find treasure in a vast maze—it needs to try different paths, but some lead nowhere. In many real-world challenges, like ...

That said, Google Cloud yesterday unveiled what it called the world’s largest public machine learning hub. Powered by Cloud TPUs (Tensor Processing Unit) v4, Google said it has a peak aggregate ...

since both problem sets and architectures vary widely across the field of machine learning—and in addition to performance, the inference side of MLPerf must also measure accuracy. If you don't ...

And now, Bright Cluster Manager also supports clusters in VMware vSphere—and goes one step further to enable high-performance clusters as a ... with strategic new applications in areas like machine ...

Using real purchase data in addition to their digital activity, businesses may create consumer groups by using K-means clustering algorithms. Unsupervised machine learning widely uses K-means ...