Question 76

You are producing a multiple linear regression model in Azure Machine Learning Studio.
Several independent variables are highly correlated.
You need to select appropriate methods for conducting effective feature engineering on all the data.
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.

Question 77

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 create a model to forecast weather conditions based on historical data.
You need to create a pipeline that runs a processing script to load data from a datastore and pass the processed data to a machine learning model training script.
Solution: Run the following code:

Does the solution meet the goal?
  • Question 78

    You create an Azure Machine Learning workspace and install the MLflow library.
    You need to tog different types of data by using the MLflow library.
    Which method should you use? To answer, select the appropriate options in the answer area.
    NOTE: Each correct selection is worth one point.

    Question 79

    You create an Azure Machine Learning workspace named workspaces. You create a Python SDK v2 notebook to perform custom model training in workspace1. You need to run the notebook from Azure Machine Learning Studio in workspace1. What should you provision first?
  • Question 80

    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.