Deploying the object detection model to an online endpoint using the Azure ML Python SDK

Just like any other ML model, a deep learning model is not useful unless it is deployed and consumers can send data for inference. In our case, it would be sending image data and getting results back containing object types and locations within the raw image.

In this section, we will show you how to use the Azure ML Python SDK to register your previously trained model and deploy it to an online endpoint for real-time inference by following these steps:

1. Open the chapter 10 notebook, which is inside the repository that you cloned by following the steps in the Technical requirements section of the chapter. Please note that our repository for this chapter uses most of the code from the original repository hosted at https://github.com/Azure/azureml-examples.
2. The first couple of cells import the required libraries and connect your notebook to the Azure ML workspace, as shown in Figure...