AI-900 practice questions 191–200

1. Question 191 · 236 in bank

   DRAG DROP - You need to use Azure Machine Learning designer to build a model that will predict automobile prices. Which type of modules should you use to complete the model? 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. Select and Place:

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Box 1: Select Columns in Dataset For Columns to be cleaned, choose the columns that contain the missing values you want to change. You can choose multiple columns, but you must use the same replacement method in all selected columns. Example: Box 2: Split data - Splitting data is a common task in machine learning. You will split your data into two separate datasets. One dataset will train the model and the other will test how well the model performed. Box 3: Linear regression - Because you want to predict price, which is a number, you can use a regression algorithm. For this example, you use a linear regression model. Reference: https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-designer-automobile-price-train-score

   Source: Adapted from community discussion — rdemontis

   References

   • Microsoft Learn

   

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2. Question 192 · 236 in bank

   Which type of machine learning should you use to identify groups of people who have similar purchasing habits?

   • Aclassification
   • Bregression
   • Cclustering

   Show answer

   Answer: C

   Explanation

   C is the answer. https://learn.microsoft.com/en-us/training/modules/create-clustering-model-azure-machine-learning-designer/2-clustering-scenarios Clustering is a form of machine learning that is used to group similar items into clusters based on their features. For example, a researcher might take measurements of penguins, and group them based on similarities in their proportions.

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn

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3. Question 193 · 236 in bank

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

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Regression is a machine learning task that is used to predict the value of the label from a set of related features. Reference: https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks

   

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4. Question 194 · 236 in bank

   Which metric can you use to evaluate a classification model?

   • Atrue positive rate
   • Bmean absolute error (MAE)
   • Ccoefficient of determination (R2)
   • Droot mean squared error (RMSE)

   Show answer

   Answer: A

   Explanation

   FYI: the concept Receiver Operating Characteristic (ROC) was developed during World War II for the analysis of radar receivers. Reference: https://stats.stackexchange.com/questions/341043/what-is-the-origin-of-the-receiver-operating-characteristic-roc-terminology

   Source: Adapted from community discussion — ssshhhh

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

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5. Question 195 · 236 in bank

   Select 2

   Which two components can you drag onto a canvas in Azure Machine Learning designer? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

   • Adataset
   • Bcompute
   • Cpipeline
   • Dmodule

   Show answer

   Answer: AD

   Explanation

   Azure Machine Learning designer lets you visually connect datasets and modules on an interactive canvas to create machine learning models.

   Source: Adapted from community discussion — ExamTopics007

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn
   • azure.microsoft.com documentation
   • azure.microsoft.com documentation

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6. Question 196 · 236 in bank

   You need to create a training dataset and validation dataset from an existing dataset. Which module in the Azure Machine Learning designer should you use?

   • ASelect Columns in Dataset
   • BAdd Rows
   • CSplit Data
   • DJoin Data

   Show answer

   Answer: C

   References

   • Microsoft Learn

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7. Question 197 · 236 in bank

   DRAG DROP - Match the types of machine learning to the appropriate scenarios. To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right. Each machine learning type may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point. Select and Place:

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Box 1: Regression - 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. Box 2: Clustering - Clustering, in machine learning, is a method of grouping data points into similar clusters. It is also called segmentation. Over the years, many clustering algorithms have been developed. Almost all clustering algorithms use the features of individual items to find similar items. For example, you might apply clustering to find similar people by demographics. You might use clustering with text analysis to group sentences with similar topics or sentiment. Box 3: Classification - Two-class classification provides the answer to simple two-choice questions such as Yes/No or True/False. Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression

   Source: Adapted from community discussion — ashayk

   

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8. Question 198 · 236 in bank

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

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Reliability and safety: AI systems need to be reliable and safe in order to be trusted. It is important for a system to perform as it was originally designed and for it to respond safely to new situations. Its inherent resilience should resist intended or unintended manipulation. Rigorous testing and validation should be established for operating conditions to ensure that the system responds safely to edge cases, and A/B testing and champion/challenger methods should be integrated into the evaluation process. An AI system's performance can degrade over time, so a robust monitoring and model tracking process needs to be established to reactively and proactively measure the model's performance and retrain it, as necessary, to modernize it. Reference: https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai

   Source: Adapted from community discussion — Pukk

   References

   • Microsoft Learn
   • Microsoft Learn

   

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9. Question 199 · 236 in bank

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

   

   This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

   Show the answer figure

   Answer: See figure below

   Explanation

   Given answer is wrong. The calculated probability of a correct image classification is typically referred to as "confidence." Confidence represents the level of certainty or probability assigned to a specific classification prediction made by a machine learning model. It indicates the model's belief in the accuracy of its prediction. For example, if a model classifies an image as a dog with a confidence of 0.85, it means the model is 85% confident that the image is correctly classified as a dog. On the other hand, accuracy is a metric that measures the overall correctness of the model's predictions. It represents the ratio of correct predictions to the total number of predictions made by the model. Accuracy alone does not provide information about the level of confidence or certainty for individual predictions.

   Source: Adapted from community discussion — rdemontis

   References

   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn
   • Microsoft Learn

   

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10. Question 200 · 236 in bank

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

    

    This is an interactive task on the real exam — a drag-and-drop, hotspot or ordering question. There is nothing to select here, so the answer is shown below for reference.

    Show the answer figure

    Answer: See figure below

    Explanation

    Reference: https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai

    Source: Adapted from community discussion — BobFar

    

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AI-900 practice, question 191. 236 questions available.