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Quiz 2025 High Hit-Rate Microsoft DP-100 Valid Exam Questions

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100% Pass Quiz 2025 Microsoft DP-100: Authoritative Designing and Implementing a Data Science Solution on Azure Valid Exam Questions

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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions (Q439-Q444):

NEW QUESTION # 439
You run an experiment that uses an AutoMLConfig class to define an automated machine learning task with a maximum of ten model training iterations. The task will attempt to find the best performing model based on a metric named accuracy.
You submit the experiment with the following code:
You need to create Python code that returns the best model that is generated by the automated machine learning task. Which code segment should you use?

Answer: A

Explanation:
Explanation
The get_output method returns the best run and the fitted model.
Reference:
https://notebooks.azure.com/azureml/projects/azureml-getting-started/html/how-to-use-azureml/automated-mach

NEW QUESTION # 440
You have an Azure Machine Learning workspace. You are running an experiment on your local computer.
You need to use MLflow Tracking to store metrics and artifacts from your local experiment runs in the workspace.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

1 - Import MLflow and Workspce classes.
2 - Load the workspace.
3 - Retrive the tracking URI and set the experiment name.
4 - Start a training run and activate the MLflow logging API.

NEW QUESTION # 441
You need to define an evaluation strategy for the crowd sentiment models.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

1 - Add new feature for retraining supervised models.
2 - Evaluate the changes in correlation between model error rate and ...
3 - Filter labeled cases for retraining using the......
Reference:
https://en.wikipedia.org/wiki/Nearest_centroid_classifier
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/sweep-clustering

NEW QUESTION # 442
You are using an Azure Machine Learning workspace. You set up an environment for model testing and an environment for production.
The compute target for testing must minimize cost and deployment efforts. The compute target for production must provide fast response time, autoscaling of the deployed service, and support real-time inferencing.
You need to configure compute targets for model testing and production.
Which compute targets should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-compute-target

NEW QUESTION # 443
Hotspot Question
You create an Azure Machine Learning workspace.
You need to detect data drift between a baseline dataset and a subsequent target dataset by using the DataDriftDetector class.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: create_from_datasets
The create_from_datasets method creates a new DataDriftDetector object from a baseline tabular dataset and a target time series dataset.
Box 2: backfill
The backfill method runs a backfill job over a given specified start and end date.
Syntax: backfill(start_date, end_date, compute_target=None, create_compute_target=False) Incorrect Answers:
List and update do not have datetime parameters.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-
datadrift/azureml.datadrift.datadriftdetector(class)

NEW QUESTION # 444
......

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