Microsoft Perform Cloud Data Science with Azure Machine Learning - 070-774 Exam Practice Test
You are building an Azure Machine Learning experiment.
You need to transform 47 numeric columns into a set of 10 linearly uncorrelated features.
Which module should you add to the experiment?
You need to transform 47 numeric columns into a set of 10 linearly uncorrelated features.
Which module should you add to the experiment?
Correct Answer: A
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You are building a classification experiment in Azure Machine Learning.
You need to ensure that you can use the Evaluate Model module the experiment.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
You need to ensure that you can use the Evaluate Model module the experiment.
Which two actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Correct Answer: B,C
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You have data about the following:
* Users
* Movies
* User ratings of the movies
You need to predict whether a user will like a particular movie. Which Matchbox recommender should you use?
* Users
* Movies
* User ratings of the movies
You need to predict whether a user will like a particular movie. Which Matchbox recommender should you use?
Correct Answer: B
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Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.
You need to transform the columns in a dataset. The resulting data must be mean centered and have a variance of L The solution must use a native module.
Which module should you use?
You need to transform the columns in a dataset. The resulting data must be mean centered and have a variance of L The solution must use a native module.
Which module should you use?
Correct Answer: H
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You have a dataset that is missing values in a column named Column3. Column3 is correlated to two columns named Column4 and Column5.
You need to improve the accuracy of the dataset, while minimizing data loss.
What should you do?
You need to improve the accuracy of the dataset, while minimizing data loss.
What should you do?
Correct Answer: C
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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 sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are working on an Azure Machine Learning experiment.
You have the dataset configured as shown in the following table.
You need to ensure that you can compare the performance of the models and add annotations to the results.
Solution: You save the output of the Score Model modules as a combined set, and then use the Project Columns module to select the MAE.
Does this meet the goal?
After you answer a question in this sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are working on an Azure Machine Learning experiment.
You have the dataset configured as shown in the following table.
You need to ensure that you can compare the performance of the models and add annotations to the results.
Solution: You save the output of the Score Model modules as a combined set, and then use the Project Columns module to select the MAE.
Does this meet the goal?
Correct Answer: B
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You have an Apache Spark cluster in Azure HDinsight. The cluster includes 200 TB in five Apache Hive tables that have multiple foreign key relationships.
You have an Azure Machine Learning model that was built by using SPARK Accelerated Failure Time (AFT) Survival Regression Model (spark-survreg).
You need to prepare the Hive data into a single table as input for the Machine Learning model. The Hive data must be prepared in the least amount of time possible.
What should you use to prepare the data?
You have an Azure Machine Learning model that was built by using SPARK Accelerated Failure Time (AFT) Survival Regression Model (spark-survreg).
You need to prepare the Hive data into a single table as input for the Machine Learning model. The Hive data must be prepared in the least amount of time possible.
What should you use to prepare the data?
Correct Answer: C
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