The Microsoft Connect(); 2018 event kicked off today, and Redmond got down to business right away announcing that the Azure Machine Learning service has reached general availability.
A cloud platform that enables developers to build, train and deploy AI models, Azure Machine Learning comes with a new feature in preview called model expandability. From now on, uses will be able to identify which input features weigh the heaviest on the predictions from the AI system.
Eric Boyd, corporate vice president at Microsoft talked about this launch:
“We’ve received a lot of positive feedback from customers who’ve been using Azure Machine Learning. It’s helping them to get their work done more quickly and efficiently than before, whether in the cloud or on-premises because it doesn’t require you to be a data scientist to use it. The automated machine learning features help select the appropriate algorithms to use.”
The core features of Azure Machine Learning are now available for everyone starting this week, including support for AI frameworks like PyTorch, TensorFlow and scikit-learn and automated hyperparameter turning
Also make the cut is the ability to deploy to both cloud and edge environments, which comes in handy with the rise in edge computing.
Microsoft also outlined new pricing, which is set to take effect on February 1, 2019.
Take a look at Azure Machine Learning here, and see how this cloud service enables computers to learn from data and experiences to act without explicit programming.
