Your success in 70-774 Exam Questions and Answers is our sole target and we develop all our 70-774 Study Guides in a way that facilitates the attainment of this target. Not only is our 70-774 Free Practice Questions material the best you can find, it is also the most detailed and the most updated. 70-774 Dumps for Microsoft 70-774 are written to the highest standards of technical accuracy.
Microsoft 70-774 Free Dumps Questions Online, Read and Test Now.
NEW QUESTION 1
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
NEW QUESTION 2
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 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 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 5
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.
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 need to alter the list of columns that will be used for predicting fraud for an input web service endpoint. The columns from the original data source must be retained while running the Machine Learning experiment.
Which module should you add after the web service input module and before the prediction module?
- A. Edit Metadata
- B. Import Data
- C. SMOTE
- D. Select Columns in Dataset
Answer: D
NEW QUESTION 6
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 7
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 8
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 9
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 10
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 11
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 12
You need to identify which columns are more predictive by using a statistical method. Which module should you use?
- A. Filter Based Feature Selection
- B. Principal Component Analysis
- C. Group Data into Bins
- D. Tune Model Hyperparameters
Answer: B
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 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 experiments.
- C. Invite users to the workspace.
- D. Delete users from the workspace.
- E. Create, open, modify, and delete web services.
- F. Access notebooks.
Answer: CDF
NEW QUESTION 14
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 15
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 Azure notebook that supports the Microsoft Cognitive Toolkit. Does this meet the goal?
- A. Yes
- B. No
Answer: B
NEW QUESTION 16
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 17
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?
- A. Replace the missing values in Column3 by using probabilistic Principal Component Analysis (PCA).
- B. Remove all of the rows that have the missing values in Column4 and Column5.
- C. Replace the missing values in Column3 with a mean value.
- D. Remove the rows that have the missing values in Column3.
Answer: A
100% Valid and Newest Version 70-774 Questions & Answers shared by 2passeasy, Get Full Dumps HERE: https://www.2passeasy.com/dumps/70-774/ (New 64 Q&As)