Anomaly detection on streaming data using Azure Databricks

From the creator

In our previous episodes of the AI Show, we've introduced to you Azure Anomaly Detector in both hosted cloud APIs and containers (Introducing Azure Anomaly Detector (https://channel9.msdn.com/Shows/AI-Show/Introducing-Azure-Anomaly-Detector) and Bring Anomaly Detector on-premise with containers support(https://channel9.msdn.com/Shows/AI-Show/Bring-Anomaly-Detector-on-premise-with-containers-support)). Our last episode (https://channel9.msdn.com/Shows/AI-Show/Anomaly-Detector-v10-Best-Practices) has shared several useful tips when you are designing your monitoring application architecture. In this episode, we're building an end-to-end solution using Anomaly Detector and Azure Databricks step by step. This solution will be able to detect numerical anomalies from streaming data coming through Azure Event Hubs. Additional Information Links: Check out the detailed tutorial for the solution we've built in this episode from https://aka.ms/adTutorialADB. Check out a simple demo on https://aka.ms/adDemo Check out the overview of the API service on https://aka.ms/AnomalyDetector. Create your first Anomaly Detector resource on Azure: https://aka.ms/adNew. Join Anomaly Detector Containers preview through https://aka.ms/adContainer. Join "Anomaly Detector Advisors" public community to connect with the product team and other members in the community through https://aka.ms/adAdvisorsJoin. Re-Visit Your Favorite Part of the Video: 00:74 - The business problem of the demo solution. 01:18 -

Published 2019-09-03 · Watch on YouTube ↗
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