Azure Machine Learning is a platform that allows users to create analytic solutions in a cloud-based environment. The service offers a simple UI and is noted for being a powerful tool for customers. The machine learning platform merges Microsoft’s cloud technology through Azure with its analytic tools such as Cortana Intelligence. Using Azure Machine Learning, developers create, trains, and roll out artificial intelligence (AI) models. Microsoft also announced upgrades to Azure Stream Analytics on Azure IoT Edge. Among the changes are a improved IoT Device Simulation Solution Accelerator, Azure IoT Remote Monitoring, and Azure Time Series Insights, and Azure Maps enhancements. In terms of Azure Machine Learning, the general availability comes with a new feature called Model Explainability. This allows users to identify which features are the heaviest on the AI system. “We’ve received a lot of positive feedback from customers who’ve been using Azure Machine Learning,” Eric Boyd, corporate vice president at Microsoft, told VentureBeat in a phone interview. “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.” Microsoft says it will introduce new pricing models for the platform on February 1, 2019.
IoT
At Connect() 2018, Microsoft also made Azure Stream Analytics (ASA) for IoT Edge. This feature makes moving analytics between cloud and edge devices more efficient. Stream Analytics can achieve this with limited connectivity and bandwidth. ASA has been in preview since last year but is now widely available to everyone starting today.
