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.

During the labs you learn the basics of PyTorch and 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 - Set an Azure Machine Learning Workspace.
Lab 2 - Create your first PyTorch Model.
Lab 3 - Pre-trained models and transfer learning.
Lab 4 - Training in the cloud.
Lab 5 - Deploy your model.

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