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| Vendor: | Microsoft |
|---|---|
| Exam Code: | DP-100 |
| Exam Name: | Designing and Implementing a Data Science Solution on Azure |
| Exam Questions: | 506 |
| Last Updated: | April 5, 2026 |
| Related Certifications: | Azure Data Scientist Associate |
| Exam Tags: | Microsoft Azure certifications, Cloud certifications Intermediate Microsoft Data Scientists and machine learning professionals |
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You plan to use automated machine learning by using Azure Machine Learning Python SDK v2 to train a regression model. You have data that has features with missing values, and categorical features with few distinct values.
You need to control whether automated machine learning automatically imputes missing values and encode categorical features as part of the training task. Which enemy of the autumn package should you use?
You plan to provision an Azure Machine Learning Basic edition workspace for a data science project.
You need to identify the tasks you will be able to perform in the workspace.
Which three tasks will you be able to perform? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
D
https://azure.microsoft.com/en-us/pricing/details/machine-learning/
You plan to use the Hyperdrive feature of Azure Machine Learning to determine the optimal hyperparameter values when training a model.
You must use Hyperdrive to try combinations of the following hyperparameter values:
* learning_rate: any value between 0.001 and 0.1
* batch_size: 16, 32, or 64
You need to configure the search space for the Hyperdrive experiment.
Which two parameter expressions should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
B: Continuous hyperparameters are specified as a distribution over a continuous range of values. Supported distributions include:
uniform(low, high) - Returns a value uniformly distributed between low and high
D: Discrete hyperparameters are specified as a choice among discrete values. choice can be:
one or more comma-separated values
a range object
any arbitrary list object
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters
You create a workspace by using Azure Machine Learning Studio.
You must run a Python SDK v2 notebook in the workspace by using Azure Machine Learning Studio.
You need to reset the state of the notebook.
Which three actions should you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
You are creating a binary classification by using a two-class logistic regression model.
You need to evaluate the model results for imbalance.
Which evaluation metric should you use?
One can inspect the true positive rate vs. the false positive rate in the Receiver Operating Characteristic (ROC) curve and the corresponding Area Under the Curve (AUC) value. The closer this curve is to the upper left corner, the better the classifier's performance is (that is maximizing the true positive rate while minimizing the false positive rate). Curves that are close to the diagonal of the plot, result from classifiers that tend to make predictions that are close to random guessing.
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