Online Access Free 070-774 Practice Test

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.Tune Model Hyperparameters
• C.Principal Component Analysis
• D.Group Data into Bins

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.

Correct 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

You have the following three training datasets for a restaurant:
You must recommend restaurant to a particular user based only on the users features.
You need to use a Matchbox Recommender to make recommendations.
How many input parameters should you specify?

• A.1
• B.3
• C.4
• D.2

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

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