Learn how to deploy and manage machine learning models in Azure Machine Learning Studio. Discover how to deploy, scale, and manage your trained models in production scenarios.
- [Instructor] The Azure Machine Learning Studio makes AI easy and approachable. With nothing to install, all you need is a modern browser and a Live ID. You will be able to create predictive models solving all sorts of interesting problems. In this course, I will not walk you through the very basics of creating an ML model. I have other courses on LinkedIn Learning that show you how to do that. The focus of this course is how to deploy and manage these models.
These skills will help you do things like deploying, logging, scaling, troubleshooting off your AI models and experiment. Hi, my name is Sahil Malik, and welcome to Azure ML: Deploying and Managing Models. AI is a big topic, and there is certainly a lot more to talk about. I enjoyed recording this course, and I hope you enjoy watching it too.
- Creating a machine learning workspace
- Creating and training an experiment
- Creating a predictive experiment
- Deploying an experiment as a web service
- Enabling logging
- Viewing logs for diagnostic purposes
- Scale and geographic deployment of your service
- Using machine learning with API management