In our previous episodes of the AI Show, we’ve learned all about the Azure Anomaly detector, how to bring the service on premises, and some awesome tips and tricks for getting the service to work well for you.

In this episode of the AI Show, Qun Ying shows us how to build an end-to-end solution using the Anomaly Detector and Azure Databricks. This step by step demo detects numerical anomalies from streaming data coming through Azure Event Hubs.

Anomaly Detection on Streaming Data Using Azure Databricks Related Links

Azure Stream Analytics is a fully managed serverless offering on Azure. With the new Anomaly Detection functions in Stream Analytics, the whole complexity associated with building and training custom machine learning (ML) models is reduced to a simple function call resulting in lower costs, faster time to value, and lower latencies.

Related links

To help securely connect to and manage IoT devices located behind firewalls or inside private networks, Azure IoT Hub team introduces Azure IoT Hub device streams offering secure general-purpose communication tunnels through the Azure cloud to IoT devices.

Check out this latest episode of the Internet of Things Show., Reza Sherafat Kazemzadeh, Sr PM for Azure IoT Hub, showcasing the new capabilities.

Learn more about IoT Hub Device Streams: https://azure.microsoft.com/en-us/blog/introducing-iot-hub-device-streams-in-public-preview/
Check out the docs: https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-device-streams-overview
Create a Free Account (Azure): https://aka.ms/aft-iot