Exam DP-100 topic 4 question 23 discussion

Actual exam question from Microsoft's DP-100

Question #: 23
Topic #: 4

You are a data scientist working for a hotel booking website company. You use the Azure Machine Learning service to train a model that identifies fraudulent transactions.
You must deploy the model as an Azure Machine Learning real-time web service using the Model.deploy method in the Azure Machine Learning SDK. The deployed web service must return real-time predictions of fraud based on transaction data input.
You need to create the script that is specified as the entry_script parameter for the InferenceConfig class used to deploy the model.
What should the entry script do?

A. Register the model with appropriate tags and properties.
B. Create a Conda environment for the web service compute and install the necessary Python packages.
C. Load the model and use it to predict labels from input data.
D. Start a node on the inference cluster where the web service is deployed.
E. Specify the number of cores and the amount of memory required for the inference compute.

Show Suggested Answer

Suggested Answer: C 🗳️

by ljljljlj at July 11, 2021, 2:21 p.m.

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ljljljlj

Highly Voted 3 years, 11 months ago

On exam 2021/7/10

upvoted 11 times

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David_Tadeu

Highly Voted 3 years, 1 month ago

Selected Answer: C

Following the given link, the workflow to deploy a model is: 1. Register the model. 2. Prepare an entry script. 3. Prepare an inference configuration. 4. Deploy the model locally to ensure everything works. 5. Choose a compute target. 6. Deploy the model to the cloud. 7. Test the resulting web service. We are in interested in step 2., and this step can be divided in: 2.1. LOADING YOUR MODEL (using a function called init()) 2.2. Running your model on input data (using a function called run())

upvoted 8 times

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