Powerful cloud-based predictive analytics • Model your way • Deploy in minutes • Expand your reach
Learn how the Azure Machine Learning service in the cloud lets you easily build, deploy, and share advanced analytics solutions.
Machine Learning offers a streamlined experience for all data scientist skill levels, from setting up with only a web browser to using drag-and-drop gestures and simple data-flow graphs to set up experiments. Azure Machine Learning Studio features a library of time-saving sample experiments, R and Python packages, and best-in-class algorithms from Microsoft businesses like Xbox and Bing. Machine Learning supports R and Python custom code, which can be dropped directly into your workspace. Easily share your experiments, so that others can pick up where you left off.
Machine Learning is designed for applied machine learning, which means that in minutes your model is live as a fully managed web service that can connect to any data, anywhere. That’s when the full power of machine learning is unleashed. As your needs change, you can easily update your solution and put it back into production, while still being able to revisit your previous results.
Now you’ve used the powerful algorithms running Microsoft businesses today, mixed and matched them with your own custom R or Python code, and created a solution worth sharing. With a click, you share your solution with the Machine Learning community in the product gallery. Then take it even further by monetizing and branding your solution on the Azure Machine Learning Marketplace and sharing it with the world.
• Get started quickly with preconfigured solutions • Tailor preconfigured solutions to meet your needs • Enhance the security of your IoT solutions • Support a broad set of operating systems and protocols • Easily connect millions of devices • Analyze and visualize large quantities of operational data • Integrate with your existing systems and applications • Scale from proof of concept to broad deployment
Set up individual identities and credentials for each of your connected devices—and help retain the confidentiality of both cloud-to-device and device-to-cloud messages. Also, selectively revoke the access rights of specific devices to maintain the integrity of your system.
Collect previously untapped data from devices and sensors, and use built-in capabilities to visualize—and act on—that data. Set up real-time analytics by using SQL-based syntax in a scalable, high-performance, and resilient way, without having to manage complex infrastructure and software. Use a vast algorithm library to extend predictive analytics solutions. And extend real-time analytics and machine-learning solutions by integrating code from languages such as R and Python directly into your workspace.
Easily integrate Azure IoT Suite with your systems and applications, including Salesforce, SAP, Oracle Database, and Microsoft Dynamics, making it simple to access your data and keep your disparate systems up to date. Send millions of messages to heterogeneous devices through a mobile push-notification engine with less development effort. Build mobile and web applications that integrate with Microsoft and third-party web APIs, and use OAuth 2.0 to build your own secure web APIs.