Developers

We continue to expand the Azure Marketplace ecosystem. For this volume, 121 new offers successfully met the onboarding criteria and went live.

Data scientists have a dynamic role. They need environments that are fast and flexible while upholding their organization’s security and compliance policies. Notebook Virtual Machine (VM), announced in May 2019, resolves these conflicting requirements while simplifying the overall experience for data scientists.

There is a lot more data in the world than can possibly be captured with even the most robust, cutting-edge technology. Edge computing and the Internet of Things (IoT) are just two examples of technologies increasing the volume of useful data.

With many IoT solutions connecting thousands of hardware endpoints, fixing security issues or upgrading functionality becomes a challenging and expensive task.

Mobility has become the center of an array of new technologies running the gamut from cloud-based algorithms and ride-sharing services, to edge cognition, assisted driving, and traffic pattern analysis – all in an effort to move people and things from one location to another more

One of the largest gatherings of healthcare IT developers will come together on the Microsoft campus next week for HL7 FHIR DevDays, with the goal of advancing the open standard for interoperable health data, called HL7® FHIR® (Fast Healthcare Interoperability Resources, pronounced “fire”).

Build more accurate forecasts with the release of capabilities in automated machine learning. Have scenarios that require have gaps in training data or need to apply contextual data to improve your forecast or need to apply lags to your features?

Azure Cognitive Services provides Text Analytics APIs that simplify extracting information from text data using natural language processing and machine learning. These APIs wrap pre-built language processing capabilities, for example, sentiment analysis, key phrase extraction, entity recognition, and language detection.

The automated machine learning capability in Azure Machine Learning service allows data scientists, analysts, and developers to build machine learning models with high scalability, efficiency, and productivity all while sustaining model quality.

For businesses today, data is indispensable. Innovative ideas in manufacturing, health care, transportation, and financial industries are often the result of capturing and correlating data from multiple sources.

Improving patient outcomes and reducing healthcare costs depends on healthcare providers such as doctors, nurses, and specialized clinician ability to access a wide range of data at the point of patient care in the form of health records, lab results, and protocols.

How do you migrate live, mission-critical data for a flagship product that must manage billions of requests with low latency and no downtime?