Exam DP-100 topic 3 question 182 discussion

Actual exam question from Microsoft's DP-100

Question #: 182
Topic #: 3

You manage an Azure Machine Learning workspace.

You experiment with an MLflow model that trains interactively by using a notebook in the workspace.

You need to log dictionary type artifacts of the experiments in Azure Machine Learning by using MLflow.

Which syntax should you use?

A. mlflow.log_input(my_dict)
B. mlflow.log_metric("my_metric", my_dict)
C. mlflow.log_metrics(my_dict)
D. mlflow.log_text("my_metric", my_dict)

Show Suggested Answer

Suggested Answer: D 🗳️

by AzureGeek79 at Oct. 12, 2024, 2:58 a.m.

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avinyc

5 months, 2 weeks ago

Selected Answer: C

Ref - https://mlflow.org/docs/latest/python_api/mlflow.html#mlflow.log_input import mlflow metrics = {"mse": 2500.00, "rmse": 50.00} # Log a batch of metrics with mlflow.start_run(): mlflow.log_metrics(metrics) # Log a batch of metrics in async fashion. with mlflow.start_run(): mlflow.log_metrics(metrics, synchronous=False)

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jl420

7 months, 2 weeks ago

Answer is C - mlflow.log_metrics(my_dict) Explanation: In MLflow, when you want to log dictionary-type artifacts that contain multiple metrics, you should use the mlflow.log_metrics() method. This method allows you to log multiple key-value pairs (i.e., a dictionary) as metrics.

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jefimija

8 months ago

log_artifact maybe?

upvoted 1 times

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AzureGeek79

8 months, 2 weeks ago

the correct answer is log_params which is not included in the available options

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