DP-100 Free Questions – Designing and Implementing a Data Science Solution on Azure

1. You need to resolve the local machine learning pipeline performance issue.

What should you do?

2. You need to select an environment that will meet the business and data requirements.

Which environment should you use?

3. You need to implement a scaling strategy for the local penalty detection data.

Which normalization type should you use?

4. You need to implement a feature engineering strategy for the crowd sentiment local models.

What should you do?

5. You need to implement a model development strategy to determine a user’s tendency to respond to an ad.

Which technique should you use?

6. You need to implement a new cost factor scenario for the ad response models as illustrated in the performance curve exhibit.

Which technique should you use?

7. You need to select a feature extraction method.

Which method should you use?

8. 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 analyzing a numerical dataset which contains missing values in several columns.

You must clean the missing values using an appropriate operation without affecting the dimensionality of the feature set.

You need to analyze a full dataset to include all values.

Solution:  Replace each missing value using the Multiple Imputation by Chained Equations (MICE) method.

Does the solution meet the goal?

9. You are conducting feature engineering to prepuce data for further analysis.

The data includes seasonal patterns on inventory requirements.

You need to select the appropriate method to conduct feature engineering on the data.

Which method should you use?

10. You are solving a classification task.

The dataset is imbalanced.

You need to select an Azure Machine Learning Studio module to improve the classification accuracy.

Which module should you use?