Episode 9 of 15
Full video series click https://aka.ms/AI-300onYouTube
This section introduces the moment when a trained model becomes actionable in real time. By deploying a model to a managed online endpoint in Azure Machine Learning, you create a scalable HTTPS API that applications, dashboards, or services can call to get instant predictions. Think of scenarios like a website that recommends products the moment a customer visits, or an app that checks fraud risk as a transaction happens. Managed online endpoints make those experiences possible—handling deployment, scaling, and endpoint management for you so your model can deliver fast, real‑time intelligence whenever it’s needed.
Immerse in rich interactive materials with self-directed learning https://aka.ms/AI-300onLearn
00:00 Video Start
00:08 Session Overview
00:55 Deploy a model to a managed online endpoint
04:35 Demo: Deploy and Endpoint
14:57 Exercise: Deploy and monitor a model in Azure Machine Learning
16:12 Knowledge Check
17:02 Summary
