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Exam DP-100 topic 3 question 154 discussion

Actual exam question from Microsoft's DP-100
Question #: 154
Topic #: 3
[All DP-100 Questions]

You create an Azure Machine Learning workspace named workspace1. The workspace contains a Python SDK v2 notebook that uses MLflow to collect model training metrics and artifacts from your local computer.

You must reuse the notebook to run on Azure Machine Learning compute instance in workspace1.

You need to continue to log metrics and artifacts from your data science code.

What should you do?

  • A. Instantiate the job class.
  • B. Instantiate the MLCIient class.
  • C. Log in to workspace1.
  • D. Configure the tracking URL.
Show Suggested Answer Hide Answer
Suggested Answer: D 🗳️
by Mikku123 at Aug. 6, 2023, 9:10 p.m.

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AnsiDP100
2 months ago
Selected Answer: D
D is the right answer.
upvoted 1 times
...
avinyc
3 months, 2 weeks ago
Selected Answer: C
C. Log in to workspace1.
upvoted 1 times
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evangelist
4 months, 2 weeks ago
Selected Answer: D
Tracking URL is mandatory, choose D
upvoted 2 times
...
sl_mslconsulting
5 months ago
Selected Answer: D
To connect MLflow to an Azure Machine Learning workspace, you need the tracking URI for the workspace. Each workspace has its own tracking URI and it has the protocol azureml://. Link: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow-configure-tracking?view=azureml-api-2&tabs=python%2Cmlflow
upvoted 2 times
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a6cb3b0
7 months ago
Selected Answer: C
You should log in to workspace 1
upvoted 1 times
...
Mikku123
1 year, 2 months ago
C is the answer !
upvoted 3 times
...
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