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5-Data-Science-In-Cloud/19-Azure/README.md

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@@ -290,18 +290,6 @@ Congratulations! You just consumed the model deployed and trained on Azure ML wi
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## [Post-lecture quiz](https://red-water-0103e7a0f.azurestaticapps.net/quiz/37)
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1. What is the reason for creating an AutoMLConfig?
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1. It is where the training and the testing data are split
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2. TRUE : It provides all the details of your AutoML experiment
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3. It is where you specify the model to be trained
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2. Which of the following metrics is supported by Automated ML for a classification task?
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1. TRUE : accuracy
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2. r2_score
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3. normalized_root_mean_error
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3. What is NOT an advantage of using the SDK?
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1. It can be used to automate multiple tasks and runs
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2. It makes it easier to programmatically edit runs
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3. It can be used throught a Graphical User Interface
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## Review & Self Study
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In this lesson, you learned how to train, deploy and consume a model to predict heart failure risk with the Azure ML SDK in the cloud. Check this [documentation](https://docs.microsoft.com/python/api/overview/azure/ml/?view=azure-ml-py?WT.mc_id=academic-40229-cxa&ocid=AID3041109) for further information about the Azure ML SDK. Try to create your own model with the Azure ML SDK.

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