Practice Free DP-100 Exam Online Questions
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are creating a new experiment in Azure Machine Learning Studio.
One class has a much smaller number of observations than the other classes in the training set.
You need to select an appropriate data sampling strategy to compensate for the class imbalance.
Solution: You use the Stratified split for the sampling mode.
Does the solution meet the goal?
- A . Yes
- B . No
You manage an Azure Machine Learning workspace. You build a model for which you must configure a Responsible Al dashboard.
Based on what you learn from the dashboard, you must perform the following activities:
• Determine what must be done to get a desirable outcome from the model.
• Identify the features that have the most direct effect on your outcome of interest.
You need to select the components to use for the Responsible Al dashboard configuration.
Which two components should you add? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
- A . error analysis
- B . counterfactuals
- C . causal
- D . explanation
HOTSPOT
You need to configure the Feature Based Feature Selection module based on the experiment requirements and datasets.
How should you configure the module properties? To answer, select the appropriate options in the dialog box in the answer area. NOTE: Each correct selection is worth one point.
You manage an Azure Machine Learning workspace. You have an environment for training jobs which uses an existing Docker image. A new version of the Docker image is available.
You need to use the latest version of the Docker image for the environment configuration by using the Azure Machine Learning SDK v2-What should you do?
- A . Modify the conda. file to specify the new version of the Docker image.
- B . Use the Environment class to create a new version of the environment.
- C . Use the create.or. update method to change the tag of the image.
- D . Change the description parameter of the environment configuration.
HOTSPOT
You create an Azure Machine Learning model to include model files and a scorning script. You must deploy the model.
The deployment solution must meet the following requirements:
• Provide near real-time inferencing.
• Enable endpoint and deployment level cost estimates.
• Support logging to Azure Log Analytics.
You need to configure the deployment solution.
What should you configure? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
You create an Azure Machine Learning workspace. You train an MLflow-formatted regression model by using tabular structured data.
You must use a Responsible Al dashboard to assess the model.
You need to use the Azure Machine Learning studio Ul to generate the Responsible A dashboard.
What should you do first?
- A . Deploy the model to a managed online endpoint.
- B . Register the model with the workspace.
- C . Create the model explanations.
- D . Convert the model from the MLflow format to a custom format.
HOTSPOT
You use Azure Machine Learning to train a machine learning model.
You use the following training script in Python to perform logging:
You must use a Python script to define a sweep job.
You need to provide the primary metric and goal you want hyperparameter tuning to optimize. NOTE: Each correct selection is worth one point.
You plan to use automated machine learning to train a regression model. You have data that has features which have missing values, and categorical features with few distinct values.
You need to configure automated machine learning to automatically impute missing values and encode categorical features as part of the training task.
Which parameter and value pair should you use in the AutoMLConfig class?
- A . featurization = ‘auto’
- B . enable_voting_ensemble = True
- C . task = ‘classification’
- D . exclude_nan_labels = True
- E . enable_tf = True
You manage an Azure Machine learning workspace.
You build a custom model you must log with Mlftow.
The custom model includes the following:
• The model is not natively supported by Mlflow.
• The model cannot be serialized in Pickle format.
• The model source code is complex.
• The Python library tor the model must be packaged with the model.
You need to create a custom model flavor to enable logging with ML. flow.
What should you use?
- A . model loader
- B . custom signatures
- C . model wrapper
- D . artifacts