070-774 무료 덤프문제 온라인 액세스

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 remove rows that have an empty value in a specific column. The solution must use a native module.
Which module should you use?

• A.Tune Model Hyperparameters
• B.Execute Python Script
• C.Import Data
• D.Normalize Data
• E.Clip Values
• F.Edit Metadata
• G.Clean Missing Data
• H.Select Columns in Dataset

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 connect the Score Model modules from each trained model as inputs for the Evaluate Model module, and use the Execute R Script module.
Does this meet the goal?

• A.No
• B.Yes

Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this scries.
Start of repeated scenario
You plan to create a predictive analytics solution for credit risk assessment and fraud prediction in Azure Machine Learning. The Machine Learning workspace for the solution will be shared with other users in your organization. You will add assets to projects and conduct experiments in the workspace.
The experiments will be used for training models that will be published to provide scoring from web services.
The experiment for fraud prediction will use Machine Learning modules and APIs to train the models and will predict probabilities in an Apache Hadoop ecosystem.
End of repeated scenario.
You plan to share the Machine Learning workspace with the other users.
You are evaluating whether to assign the User role or the Owner role to several of the users.
Which three actions can be performed by the users who are assigned the User role? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

• A.Create, open, modify, and delete datasets.
• B.Create, open, modify, and delete web services.
• C.Create, open, modify, and delete experiments.
• D.Access notebooks.
• E.Delete users from the workspace.
• F.Invite users to the workspace.

You have the following HiveQL query in an Import Data module.

Which type of operation is being performed?

• A.random sampling by groups
• B.stratified sampling
• C.sampling a bucketized table
• D.uniform random sampling

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?

• A.Related Items
• B.Related Users
• C.Rating Prediction
• D.Item Recommendation