Use TimeXtender to build a modern data estate that is ready for cloud scale analytics using a drag-and-drop user interface, with definitions stored in a metadata repository.
Learn how to build, deploy, and monitor a machine learning model for employee attrition that can be integrated with external applications using Databricks and Kubernetes.
Learn how an IoT measure and control loop keeps an IoT device within the tolerable range of setpoint configuration, through a real-time, closed-loop control process.
Often machine learning (ML) problems are too complex for a single ML model to solve. Learn about many models machine learning at scale in Azure with Spark.