NEW QUESTION 1
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 designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs. You plan to detect the presence of trees in the photographs.
You need to ensure that your model supports the following: Solution: You create an endpoint to the Computer vision API. Does this meet the goal?

• A. Yes
• B. No

Answer: B

NEW QUESTION 2
You are performing exploratory analysis of files that are encoded in a complex proprietary format. The format requires disk intensive access to several dependent files in HDFS.
You need to build an Azure Machine Learning model by using a canopy clustering algorithm. You must ensure that changes to proprietary file formats can be maintained by using the least amount of effort.
Which Machine Learning library should you use?

• A. MicrosoftML
• B. scikit-learn
• C. SparkR
• D. Mahout

Answer: C

NEW QUESTION 3
You have the following HiveQL query in an Import Data module.

Which type of operation is being performed?

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

Answer: D

NEW QUESTION 4
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 use only one percent of an Apache Hive data table by conducting random sampling by groups. Which module should you use?

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

Answer: A

Explanation: References:
https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/sample-data-hive

NEW QUESTION 5
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 have an Azure ML experiment that contains an intermediate dataset. You need to explore data from the intermediate dataset by using Jupyter.
Solution: In Azure Mt Studio, you use the Save as dataset option, and then open the output in a new notebook. Does this meet the goal?

• A. Yes
• B. No

Answer: A

NEW QUESTION 6
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. Execute Python Script
• B. Tune Model Hyperparameters
• C. Normalize Data
• D. Select Columns in Dataset
• E. Import Data
• F. Edit Metadata
• G. Clip Values
• H. Clean Missing Data

Answer: H

Explanation: References:
https://blogs.msdn.microsoft.com/azuredev/2021/05/27/data-cleansing-tools-in-azure-machine-learning/

NEW QUESTION 7
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 series.
A travel agency named Margie’s Travel sells airline tickets to customers in the United States.
Margie’s Travel wants you to provide insights and predictions on flight delays. The agency is considering implementing a system that will communicate to its customers as the flight departure nears about possible delays due to weather conditions. The flight data contains the following attributes:
The weather data contains the following attributes: AirportID, ReadingDate (YYYY/MM/DD HH), SkyConditionVisibility, WeatherType, WindSpeed, StationPressure, PressureChange, and HourlyPrecip.
You need to use historical data about on-time flight performance and the weather data to predict whether the departure of a scheduled flight will be delayed by more than 30 minutes.
Which method should you use?

• A. clustering
• B. linear regression
• C. classification
• D. anomaly detection

Answer: C

Explanation: References:
https://gallery.cortanaintelligence.com/Experiment/Binary-Classification-Flight-delay-prediction-3

NEW QUESTION 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 sections, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are designing an Azure Machine Learning workflow.
You have a dataset that contains two million large digital photographs. You plan to detect the presence of trees in the photographs.
You need to ensure that your model supports the following:
Solution: You create a Machine Learning experiment that implements the Multiclass Neural Network module. Does this meet the goal?

• A. Yes
• B. No

Answer: A

NEW QUESTION 9
You have an Azure Machine Learning experiment.
You discover that a model causes many errors in a production dataset. The model causes only few errors in the training data.
What is the cause of the errors?

• A. overfitting
• B. generalization
• C. underfitting
• D. a simple predictor

Answer: A

NEW QUESTION 10
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 have an Azure ML experiment that contains an intermediate dataset. You need to explore data from the intermediate dataset by using Jupyter.
Solution: You add a web service input to retrieve the data for the data source, and then add the Execute R Script module.
Does this meet the goal?

• A. Yes
• B. No

Answer: B

NEW QUESTION 11
You are working on an Azure Machine Learning experiment that uses four different logistic regression algorithms. You are evaluating the algorithms based on the data in the following table.

Which model produces predictions that are the closest to the actual outcomes?

• A. Model 1
• B. Model 2
• C. Model 3
• D. Model 4

Answer: A

NEW QUESTION 12
From the Cortana Intelligence Gallery, you deploy a solution. You need to modify the solution.
What should you use?

• A. Azure Stream Analytics
• B. Microsoft Power BI Desktop
• C. Azure Machine Learning Studio
• D. R Tools for Visual Studio

Answer: C

Explanation: References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/gallery-experiments

NEW QUESTION 13
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 series.
A travel agency named Margie’s Travel sells airline tickets to customers in the United States.
Margie’s Travel wants you to provide insights and predictions on flight delays. The agency is considering implementing a system that will communicate to its customers as the flight departure nears about possible delays due to weather conditions. The flight data contains the following attributes:
The weather data contains the following attributes: AirportID, ReadingDate (YYYY/MM/DD HH), SkyConditionVisibility, WeatherType, WindSpeed, StationPressure, PressureChange, and HourlyPrecip.
You have an untrained Azure Machine Learning model that you plan to train to predict flight delays.
You need to assess the variability of the dataset and the reliability of the predictions from the model. Which module should you use?

• A. Cross-Validate Model
• B. Evaluate Model
• C. Tune Model Hyperparameters
• D. Train Model
• E. Score Model

Answer: A

Explanation: References:
https://msdn.microsoft.com/en-us/library/azure/dn905852.aspx

NEW QUESTION 14
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 series.
Start of repeated scenario
You plan to use Azure platform tools to detect and analyze food items in smart refrigerators. To provide families with an integrated experience for grocery shopping and cooking, the refrigerators will connect to other smart appliances, such as stoves and microwave ovens, on a LAN.
You plan to build an object recognition model by using the Microsoft Cognitive Toolkit. The object recognition model will receive input from the connected devices and send results to applications.
The training data will be derived from more than 10 TB of images. You will convert the raw images to the sparse format.
End of repeated scenario.
You need to ensure that a web service endpoint can receive image data and use an object recognition model to return the expected object and the confidence level of the model. The solution must minimize the effort required to generate the client code to access the web service.
Which resource should you use?

• A. the edX Data Science Learning Dashboard
• B. Azure Machine Learning Studio
• C. Cortana Intelligence Gallery
• D. the Data Science Virtual Machine

Answer: B

NEW QUESTION 15
You need to create a training set for use with a linear regression model, and then to test the training set.
How should you create the training set? To answer, drag the appropriate modules to the correct locations. Each module may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation: C:UserswkDesktopmudassarUntitled.jpg

NEW QUESTION 16
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 series.
Start of repeated scenario
You plan to use Azure platform tools to detect and analyze food items in smart refrigerators. To provide families with an integrated experience for grocery shopping and cooking, the refrigerators will connect to other smart appliances, such as stoves and microwave ovens, on a LAN.
You plan to build an object recognition model by using the Microsoft Cognitive Toolkit. The object recognition model will receive input from the connected devices and send results to applications.
The training data will be derived from more than 10 TB of images. You will convert the raw images to the sparse format.
End of repeated scenario.
The image files to train the object recognition model are stored in a Microsoft SQL Server 2021 Standard edition database on an Azure virtual machine (VM).
You need to support R packages that can use full parallel threading and processing for RevoScaleR.
How should you implement R? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION 17
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?

• A. a Hive user-defined function (UDF)
• B. Spark SQL
• C. the GPU
• D. Java Mapreduce jobs

Answer: A

NEW QUESTION 18
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.

• A. Connect the input of the Score Model modules to the output of the Evaluate Model module.
• B. Connect the input of the Score Model modules to the output of the Train Model modules and the output Split Data modules.
• C. Connect the output of the Score Model modules to the input of the Evaluate Model module.
• D. Connect the output of the Score Model modules to the input of the Train Model modules and the input of the Split Data modules.

Answer: AB