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Exam DP-100 topic 3 question 87 discussion

Actual exam question from Microsoft's DP-100
Question #: 87
Topic #: 3
[All DP-100 Questions]

HOTSPOT -
You are running a training experiment on remote compute in Azure Machine Learning.
The experiment is configured to use a conda environment that includes the mlflow and azureml-contrib-run packages.
You must use MLflow as the logging package for tracking metrics generated in the experiment.
You need to complete the script for the experiment.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

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Suggested Answer:
Box 1: import mlflow -
Import the mlflow and Workspace classes to access MLflow's tracking URI and configure your workspace.
Box 2: mlflow.start_run()
Set the MLflow experiment name with set_experiment() and start your training run with start_run().
Box 3: mlflow.log_metric(' ..')
Use log_metric() to activate the MLflow logging API and begin logging your training run metrics.
Box 4: mlflow.end_run()
Close the run:
run.endRun()
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow

Comments

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dev2dev
Highly Voted 2 years, 8 months ago
Correct https://www.mlflow.org/docs/latest/python_api/mlflow.html
upvoted 15 times
Anty85
2 years, 8 months ago
Yup. https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-mlflow
upvoted 6 times
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Yuriy_Ch
Most Recent 8 months, 3 weeks ago
Exactly this question was on exam 07/March/2023
upvoted 1 times
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ABHINAVY27
1 year, 6 months ago
You don't see end_run in the docs coz they use 'while mlflow.start_run' to avoid using it @ TheYazan
upvoted 1 times
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TheYazan
1 year, 8 months ago
I don't see any use of end_run in the docs
upvoted 1 times
TheYazan
1 year, 8 months ago
and what are the libraries to log metrics?
upvoted 1 times
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AI247
2 years ago
on exam 5 Nov 2021
upvoted 2 times
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hargur
2 years, 1 month ago
on 19Oct2021
upvoted 3 times
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