Question 86
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 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.
Question 87
You are working on a classification task. You have a dataset indicating whether a student would like to play soccer and associated attributes. The dataset includes the following columns:
You need to classify variables by type.
Which variable should you add to each category? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
You need to classify variables by type.
Which variable should you add to each category? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Question 88
Drag and Drop Question
You have an Azure Machine Learning workspace named WS1.
You plan to use WS1 to train two models named model1 and model2. For model1, you plan to use automated machine learning. For model2, you plan to use Azure Machine Learning designer.
You need to determine the compute targets you should use to train each model. Your solution must ensure the following:
- The compute target for model1 supports auto-shutdown/auto-start based on a schedule.
- The compute target for model2 supports the use of low-priority Azure
Virtual Machines.
Which compute targets should you use? To answer, move the appropriate compute targets to the correct model. You may use each compute target once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
You have an Azure Machine Learning workspace named WS1.
You plan to use WS1 to train two models named model1 and model2. For model1, you plan to use automated machine learning. For model2, you plan to use Azure Machine Learning designer.
You need to determine the compute targets you should use to train each model. Your solution must ensure the following:
- The compute target for model1 supports auto-shutdown/auto-start based on a schedule.
- The compute target for model2 supports the use of low-priority Azure
Virtual Machines.
Which compute targets should you use? To answer, move the appropriate compute targets to the correct model. You may use each compute target once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Question 89
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?
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 90
You are creating an experiment by using Azure Machine Learning Studio.
You must divide the data into four subsets for evaluation. There is a high degree of missing values in the data.
You must prepare the data for analysis.
You need to select appropriate methods for producing the experiment.
Which three modules should you run in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
You must divide the data into four subsets for evaluation. There is a high degree of missing values in the data.
You must prepare the data for analysis.
You need to select appropriate methods for producing the experiment.
Which three modules should you run in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
