Deploy a Model as a Service with Azure
In this lab, you’ll practice deploying, consuming, and troubleshooting a Machine Learning model. When you’re finished with this lab, you’ll have experience using Azure Machine Learning studio to deploy a model.
Terms and conditions apply.
Access Jupyter Notebook in Azure Machine Learning Studio
Launch Azure Machine Learning studio and download files to prepare your environment.
Prepare Model for Deployment
You will run Python code in Jupyter notebook to prepare an existing model for deployment.
Deploy the Model to an Azure Container Instance (ACI)
You will deploy the prepared model to a new Azure Container Instance (ACI)
Review Model Deployment Logs for Troubleshooting
You will review the deployment logs to troubleshoot or verify the successful deployment
Consume a Web Service to Test the Model
You will test the model by downloading test data and loading it into the model.
Provided environment for hands-on practice
We will provide the credentials and environment necessary for you to practice right within your browser.
Follow along with the author’s guided walkthrough and build something new in your provided environment!
Did you know?
On average, you retain 75% more of your learning if you get time for practice.
- Basic familiarity with Python
- Basic familiarity with Azure CLI