In this hands-on lab you are going to build and deploy your own trained vision model to a highly scalable endpoint using Azure Machine Learning. You start with setting up your cloud workspace and learn how to manage your data and make it reusable. Next you will train a PyTorch model using the transfer learning approach and finally you deploy the model wrapped in an API in a managed endpoint.
At the end of this hands-on lab you have gone through the complete life-cycle of a model, from data to deployment using the Azure Machine Learning platform.
- Lab 1 - Setup your development environment
- Lab 2 - Setup Azure Machine Learning
- Lab 3 - Build and deploy a PyTorch model
- Lab 4 - Build a trainings Pipeline