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 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 Convert to CSV module to the Azure ML experiment and then open the module output in a new notebook.
Does this meet the goal?

• A. Yes
• B. No

Answer: A

NEW QUESTION 2
You are building an Azure Machine Learning experiment.
You need to transform a string column that has 47 distinct values into a binary indicator column. The solution must use the One-vs-All Multiclass model.
Which module should you use?

• A. Select Column Transform
• B. Convert to Indicator Values
• C. Group Categorical Values
• D. Edit Metadata

Answer: B

NEW QUESTION 3
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 preprocess the training data by using a Principal Component Analysis (PCA) algorithm in the least amount of time possible. Which implementation method should you use?

• A. Azure HDInsight using HiveML
• B. Azure Machine Learning Studio and a custom Execute Python Script module
• C. Azure HDInsight using Microsoft R Server
• D. Azure Machine Learning Studio with a custom Execute R Script module

Answer: C

NEW QUESTION 4
You are building an Azure Machine Learning solution for an online retailer.
When a customer selects a product, you need to recommend products that the customer might like to purchase at the same time. The recommendation should be based on what other customers purchased when they purchased the same product.
Which model should you use?

• A. Collaborative filtering
• B. Boosted Decision Tree Regression model
• C. Two-Class boosted decision tree
• D. K-Means Clustering

Answer: A

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 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 then save the results as a dataset.
Does this meet the goal?

• A. Yes
• B. No

Answer: A

Explanation: References:
https://msdn.microsoft.com/en-us/library/azure/dn905915.aspx

NEW QUESTION 6
You plan to use Azure Machine Learning to develop a predictive model. You plan to include an Execute Python Script module.
What capability does the module provide?

• A. Outputting a file to a network location.
• B. Performing interactive debugging of a Python script.
• C. Saving the results of a Python script run in a Machine Learning environment to a local file.
• D. Visualizing univariate and multivariate summaries by using Python code.

Answer: D

Explanation: References:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/execute-python-scripts

NEW QUESTION 7
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 have a non-tabular file that is saved in Azure Blob storage.
You need to download the file locally, access the data in the file, and then format the data as a dataset. 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: E

Explanation: References:
https://msdn.microsoft.com/en-us/library/azure/mt674698.aspx

NEW QUESTION 8
You work for a company that has retail department stores.
You are developing an Azure Machine Learning experiment to predict seasonal sales. You need to address a model overfitting issue by using the following two solutions:
• Solution 1: Controls the penalty for complexity, which, when successful, prevents overfitting
• Solution 2: Separates model selection from testing, causing a more conservative estimate of generalization Which method should you use for each solution? To answer, drag the appropriate methods to the correct
solutions. Each method 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:

NEW QUESTION 9
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 consolidate the output of the Score Model modules by using the Add Rows module, and then
use the Execute R Script module.
Does this meet the goal?

• A. Yes
• B. No

Answer: A

Explanation: References:
https://msdn.microsoft.com/en-us/library/azure/dn905915.aspx

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 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 Decision Jungle module. Does this meet the goal?

• A. Yes
• B. No

Answer: B

NEW QUESTION 11
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 deploy a multiple-service solution that was developed already and published by other users in the Microsoft development community.
What should you use?

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

Answer: C

NEW QUESTION 12
You plan to use the Data Science Virtual Machine for development, but you are unfamiliar with R scripts. You need to generate R code for an experiment.
Which IDE should you use?

• A. XgBoost
• B. Rattle
• C. Vowpal Wabbit
• D. R Tools for Visual Studio

Answer: C

Explanation: References:
https://docs.microsoft.com/en-us/azure/machine-learning/data-science-virtual-machine/provision-vm

NEW QUESTION 13
You deploy Microsoft Data Management Gateway.
You plan to use the Import Data module in Azure Machine Learning Studio to import data from an on-premises Microsoft SQL Server instance.
Which operation can you perform?

• A. Write the data back to the on-premises SQL Server instance.
• B. Filter the data as the data is being read by using the Import Data module.
• C. Run a Transact-SQL query and use SQL views to filter the data as the data is being read.
• D. Access the on-premises SQL Server instance without using credentials, and then import the data.

Answer: D

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 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.
The users will use different data sources that follow a standard format. The users will receive results in a standard format by using the fraud prediction web service. The results will be saved to a location specified by the users.
You need to provide the users with the ability to get results for different risk tolerances without affecting the calculation of the model. Which three modules should be configured to use the Web Service Parameters? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

• A. Evaluate Model
• B. Import Data
• C. Select Columns in Dataset
• D. Export Data
• E. Time Series Anomaly Detection

Answer: ABD

NEW QUESTION 15
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 remove the bias and to identify the columns in the input dataset that have the greatest predictive power.
Which module should you use for each requirement? To answer, drag the appropriate modules to the correct requirements. 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: References:
https://gallery.cortanaintelligence.com/Experiment/Binary-Classification-Flight-delay-prediction-3 https://msdn.microsoft.com/library/azure/038d91b6-c2f2-42a1-9215-1f2c20ed1b40

NEW QUESTION 16
The manager of a call center reports that staffing the center is difficult because the number of calls is unpredictable. You have historical data that contains information about the calls.
You need to build an Azure Machine Learning experiment to predict the number of total calls each hour. Which model should you use?

• A. Multiclass Logistic Regression
• B. Boosted Decision Tree Regression
• C. Decision Forest Regression
• D. Poisson Regression

Answer: D

NEW QUESTION 17
You have an Azure Machine Learning environment. You are evaluating whether to use R code or Python.
Which three actions can you perform by using both R code and Python in the Machine Learning environment? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

• A. Preprocess, cleanse, and group data.
• B. Score a training model.
• C. Create visualizations.
• D. Create an untrained model that can be used with the Train Model module.
• E. Implement feature ranking.

Answer: ABC

NEW QUESTION 18
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. Yes
• B. No

Answer: A

Explanation: References:
https://msdn.microsoft.com/en-us/library/azure/dn905915.aspx