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You use Azure Machine Learning designer to publish an inference pipeline.
Which two parameters should you use to consume the pipeline? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. the model name
B. the training endpoint
C. the authentication key
D. the REST endpoint
Correct Answer: AD
Explanation/Reference:
A: The trained model is stored as a Dataset module in the module palette. You can find it under My Datasets.
Azure Machine Learning designer lets you visually connect datasets and modules on an interactive canvas to create machine learning models.
D: You can consume a published pipeline in the Published pipelines page. Select a published pipeline and find the REST endpoint of it.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-run-batch-predictions-designer https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer
Now you can test your deployed service from a client application – in this case, you’ll use the code in the cell below to simulate a client application.
1. On the Endpoints page, open the predict-auto-price real-time endpoint.
2. When the predict-auto-price endpoint opens, view the Consume tab and note the following information there. You need this to connect to your deployed service from a client application.
You can consume a published pipeline on the Published pipelines page. Select a published pipeline and find the REST endpoint of it.
To consume the pipeline, you need:
✑ The REST endpoint for your service
✑ The Primary Key for your service
Reference: Run batch predictions using Azure Machine Learning designer
Ans C and D