AI-900 practice questions 201–210

1. Question 201 · 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

   Based on this statement from the referenced article: Feature selection: The process of selecting the key subset of features to reduce the dimensionality of the training problem. Feature selection is the answer since feature engineering is the creation of NEW features from raw data to capture additional information not easily apparent in the original feature set.

   Source: Adapted from community discussion — rfiuvcfns

   References

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

   

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2. Question 202 · 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/machine-learning/how-to-label-data

   References

   • Microsoft Learn

   

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3. Question 203 · 236 in bank

   HOTSPOT - You have an Azure Machine Learning model that predicts product quality. The model has a training dataset that contains 50,000 records. A sample of the data is shown in the following table.

   

   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:

   

   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/machine-learning/component-reference/filter-based-feature-selection

   Source: Adapted from community discussion — BobFar

   

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4. Question 204 · 236 in bank

   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:

   

   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/learn/modules/create-regression-model-azure-machine-learning-designer/5-create-training-pipeline https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/introduction https://docs.microsoft.com/en-us/learn/modules/create-clustering-model-azure-machine-learning-designer/1-introduction

   Source: Adapted from community discussion — zellck

   References

   • Microsoft Learn
   • Microsoft Learn

   

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5. Question 205 · 236 in bank

   Select 2

   Which two actions are performed during the data ingestion and data preparation stage of an Azure Machine Learning process? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

   • ACalculate the accuracy of the model.
   • BScore test data by using the model.
   • CCombine multiple datasets.
   • DUse the model for real-time predictions.
   • ERemove records that have missing values.

   Show answer

   Answer: CE

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6. Question 206 · 236 in bank

   You need to predict the animal population of an area. Which Azure Machine Learning type should you use?

   • Aregression
   • Bclustering
   • Cclassification

   Show answer

   Answer: A

   References

   • Microsoft Learn

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7. Question 207 · 236 in bank

   Select 2

   Which two languages can you use to write custom code for Azure Machine Learning designer? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.

   • APython
   • BR
   • CC#
   • DScala

   Show answer

   Answer: AB

   Explanation

   "Build and train machine learning models with state-of-the art machine learning and deep learning algorithms, including those for computer vision, text analytics, recommendations, and anomaly detection. Drag and drop modules for no-code models or customize using Python and R code." as per the link given: https://azure.microsoft.com/en-us/products/machine-learning/designer/#features

   Source: Adapted from community discussion — arska

   References

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

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8. Question 208 · 236 in bank

   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:

   

   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: Yes - For regression problems, the label column must contain numeric data that represents the response variable. Ideally the numeric data represents a continuous scale. Box 2: No - K-Means Clustering - Because the K-means algorithm is an unsupervised learning method, a label column is optional. If your data includes a label, you can use the label values to guide selection of the clusters and optimize the model. If your data has no label, the algorithm creates clusters representing possible categories, based solely on the data. Box 3: No - For classification problems, the label column must contain either categorical values or discrete values. Some examples might be a yes/no rating, a disease classification code or name, or an income group. If you pick a noncategorical column, the component will return an error during training. Reference: https://docs.microsoft.com/en-us/azure/machine-learning/component-reference/train-model https://docs.microsoft.com/en-us/azure/machine-learning/component-reference/k-means-clustering

   Source: Adapted from community discussion — lphan911

   

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9. Question 209 · 236 in bank

   DRAG DROP - Match the types of AI workloads to the appropriate scenarios. To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload 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 3: Natural language processing Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization. Reference: https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

   Source: Adapted from community discussion — gargaditya

   References

   • Microsoft Learn
   • Microsoft Learn

   

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10. Question 210 · 236 in bank

    Your company wants to build a recycling machine for bottles. The recycling machine must automatically identify bottles of the correct shape and reject all other items. Which type of AI workload should the company use?

    • Aanomaly detection
    • Bconversational AI
    • Ccomputer vision
    • Dnatural language processing

    Show answer

    Answer: C

    Explanation

    C is correct. Anomaly detection is unsupervised learning that detect "deviation" from norm. To correctly identify the "correct" plastic bottle, computer vision should be used.

    Source: Adapted from community discussion — fatrapb1t

    References

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

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AI-900 practice, question 201. 236 questions available.