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| Section | Objectives |
|---|---|
| Topic 1: Design and prepare a machine learning solution | - Select appropriate Azure services for machine learning workloads - Manage compute and data assets - Plan and configure Azure Machine Learning workspace |
| Topic 2: Optimize and manage models | - Improve model performance - Track experiments and manage model lifecycle |
| Topic 3: Explore and analyze data | - Ingest and prepare data for modeling - Perform exploratory data analysis |
| Topic 4: Train machine learning models | - Train models using Azure Machine Learning - Tune hyperparameters and evaluate models |
| Topic 5: Deploy and consume models | - Monitor deployed models and endpoints - Deploy models to endpoints |
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NEW QUESTION # 30
You are determining if two sets of data are significantly different from one another by using Azure Machine Learning Studio.
Estimated values in one set of data may be more than or less than reference values in the other set of data.
You must produce a distribution that has a constant. Type I error as a function of the correlation.
You need to produce the distribution.
Which type of distribution should you produce?
Answer: A
Explanation:
Choose a one-tail or two-tail test. The default is a two-tailed test. This is the most common type of test, in which the expected distribution is symmetric around zero.
Example: Type I error of unpaired and paired two-sample t-tests as a function of the correlation.
The simulated random numbers originate from a bivariate normal distribution with a variance of 1.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/test-hypothesis-using-t-test
https://en.wikipedia.org/wiki/Student%27s_t-test
NEW QUESTION # 31
You are the owner of an Azure Machine Learning workspace.
You must prevent the creation or deletion of compute resources by using a custom role. You must allow all other operations inside the workspace.
You need to configure the custom role.
How should you complete the configuration? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Microsoft.MachineLearningServices/workspaces/*/read
Reader role: Read-only actions in the workspace. Readers can list and view assets, including datastore credentials, in a workspace. Readers can't create or update these assets.
Box 2: Microsoft.MachineLearningServices/workspaces/*/write
If the roles include Actions that have a wildcard (*), the effective permissions are computed by subtracting the NotActions from the allowed Actions.
Box 3: Box 2: Microsoft.MachineLearningServices/workspaces/computes/*/delete Box 4: Microsoft.MachineLearningServices/workspaces/computes/*/write Reference:
https://docs.microsoft.com/en-us/azure/role-based-access-control/overview#how-azure-rbac-determines-if-a- user-has-access-to-a-resource
NEW QUESTION # 32
You have a binary classifier that predicts positive cases of diabetes within two separate age groups.
The classifier exhibits a high degree of disparity between the age groups.
You need to modify the output of the classifier to maximize its degree of fairness across the age groups and meet the following requirements:
* Eliminate the need to retrain the model on which the classifier is based.
* Minimize the disparity between true positive rates and false positive rates across age groups.
Which algorithm and panty constraint should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
NEW QUESTION # 33
You are analyzing the asymmetry in a statistical distribution.
The following image contains two density curves that show the probability distribution of two datasets.
Use the drop-down menus to select the answer choice that answers each question based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/compute-elementary-statistics
NEW QUESTION # 34
You are performing a classification task in Azure Machine learning Studio.
You must prepare balanced testing and training samples based on a provided data set.
Warning samples based on a provided data set.
You need to split the data with a 0.75:0.25.
Which value should you use for each parameter? To answer, select the appropriate options m the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 35
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