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Exercise : Exam AI 900 Microsoft Azure AI Fundamentals MCQ Questions and Answers

Question 1

Which metric can you use to evaluate a classification model?

A.  
B.  
C.  
D.  

Correct Answer : B. true positive rate

Description :
What does a good model look like?
An ROC curve that approaches the top left corner with 100% true positive rate and 0% false positive rate will be the best model. A random model would display as a flat line from the bottom left to the top right corner. Worse than random would dip below the y=x line.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-ml#classification

Question 2

Which type of machine learning should you use to predict the number of gift cards that will be sold next month?

A.  
B.  
C.  

Correct Answer : B. regression

Description :
In the most basic sense, regression refers to prediction of a numeric target.
Linear regression attempts to establish a linear relationship between one or more independent variables and a numeric outcome, or dependent variable.
You use this module to define a linear regression method, and then train a model using a labeled dataset. The trained model can then be used to make predictions.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression

Question 3

DRAG DROP -
Match the principles of responsible AI to appropriate requirements.
To answer, drag the appropriate principles from the column on the left to its requirement on the right. Each principle 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.
Select and Place:

A.  
B.  
C.  
D.  

Question 4

HOTSPOT - For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:

A.  
B.  
C.  
D.  

Correct Answer : C. Yes, No, Yes, No

Description :

Box 1: Yes -
Automated machine learning, also referred to as automated ML or AutoML, is the process of automating the time consuming, iterative tasks of machine learning model development. It allows data scientists, analysts, and developers to build ML models with high scale, efficiency, and productivity all while sustaining model quality.

Box 2: No -

Box 3: Yes -
During training, Azure Machine Learning creates a number of pipelines in parallel that try different algorithms and parameters for you. The service iterates through
ML algorithms paired with feature selections, where each iteration produces a model with a training score. The higher the score, the better the model is considered to "fit" your data. It will stop once it hits the exit criteria defined in the experiment.

Box 4: No -
Apply automated ML when you want Azure Machine Learning to train and tune a model for you using the target metric you specify.
The label is the column you want to predict.
Reference:
https://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features

Question 5

You are building an AI-based app.
You need to ensure that the app uses the principles for responsible AI.
Which two principles should you follow? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Implement an Agile software development methodology
B. Implement a process of AI model validation as part of the software review process Most Voted
C. Establish a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy officer Most Voted
D. Prevent the disclosure of the use of AI-based algorithms for automated decision making

A.  
B.  
C.  
D.  

Question 6

HOTSPOT -
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Hot Area:

A.  
B.  
C.  
D.  

Correct Answer : A. No, Yes, No

Description :

Anomaly detection encompasses many important tasks in machine learning:
Identifying transactions that are potentially fraudulent.
Learning patterns that indicate that a network intrusion has occurred.
Finding abnormal clusters of patients.
Checking values entered into a system.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection

Question 7

Which analytical task of the computer vision service returns bounding box coordinates?

A.  
B.  
C.  
D.  

Correct Answer : C. object detection

Description :
Detecting objects identifies common objects and, for each, returns bounding box coordinates. Image categorization assigns a category to an image, but it does not return bounding box coordinates. Tagging involves associating an image with metadata that summarizes the attributes of the image, but it does not return bounding box coordinates. OCR detects printed and handwritten text in images, but it does not return bounding box coordinates.
References :
Get started with image analysis on Azure - Training | Microsoft Learn

Question 8

An electricity utility company wants to develop a mobile app for its customers to monitor their energy use and to display their predicted energy use for the next 12 months. The company wants to use machine learning to provide a reasonably accurate prediction of future energy use by using the customers’ previous energy-use data.

Which type of machine learning is this?

A.  
B.  
C.  
D.  

Correct Answer : D. regression

Description :
Regression is a machine learning scenario that is used to predict numeric values. In this example, regression will be able to predict future energy consumption based on analyzing historical time-series energy data based on factors, such as seasonal weather and holiday periods. Multiclass classification is used to predict categories of data. Clustering analyzes unlabeled data to find similarities present in the data. Classification is used to predict categories of data.
References :
Create a regression model with Azure Machine Learning designer - Training | Microsoft Learn

Question 9

HOTSPOT - To complete the sentence, select the appropriate option in the answer area.
Hot Area:

A.  
B.  
C.  

Correct Answer : A. classification

Description :

Two-class classification provides the answer to simple two-choice questions such as Yes/No or True/False.

Question 10

You build a machine learning model by using the automated machine learning user interface (UI).
You need to ensure that the model meets the Microsoft transparency principle for responsible AI.
What should you do?

A.  
B.  
C.  
D.  

Correct Answer : C. Enable Explain best model

Description :
Model Explain Ability.
Most businesses run on trust and being able to open the ML ג€black boxג€ helps build transparency and trust. In heavily regulated industries like healthcare and banking, it is critical to comply with regulations and best practices. One key aspect of this is understanding the relationship between input variables (features) and model output. Knowing both the magnitude and direction of the impact each feature (feature importance) has on the predicted value helps better understand and explain the model. With model explain ability, we enable you to understand feature importance as part of automated ML runs.
Reference:
https://azure.microsoft.com/en-us/blog/new-automated-machine-learning-capabilities-in-azure-machine-learning-service/

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