The focus is applications that sit atop the company's existing cloud-based commercial apps, making deploying and consuming machine learning as easy as possible for admin and IT worker.

Machine learning and its subsets are useful for a wide range of problems, tasks, and applications. There’s computer vision, which allows computers to “see” and make sense of images and videos.

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

Machine learning is a rapidly growing field with endless potential applications. In the next few years, we will see machine learning transform many industries, including manufacturing, retail and ...

Head-to-head comparison: Azure Machine Learning vs. IBM Watson Model training and development Azure ML offers more features for data preparation, transformation, normalization and model training ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing ...

David S Watson, Jenny Krutzinna, Ian N Bruce, Christopher EM Griffiths, Iain B McInnes, Michael R Barnes, Luciano Floridi, Clinical applications of machine learning algorithms, BMJ: British Medical ...

Proximal algorithms are useful for obtaining solutions to difficult optimization problems, especially those involving nonsmooth or composite objective functions. A proximal algorithm is one whose ...