Exams > Microsoft > AI-900: Microsoft Azure AI Fundamentals
AI-900: Microsoft Azure AI Fundamentals
Page 4 out of 16 pages Questions 31-40 out of 153 questions
Question#31

HOTSPOT -
To complete the sentence, select the appropriate option in the answer area.
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Answer:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-label-data

Question#32

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.
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Answer:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/component-reference/filter-based-feature-selection

Question#33

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.
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Answer:
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

Question#34

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.

  • A. Calculate the accuracy of the model.
  • B. Score test data by using the model.
  • C. Combine multiple datasets.
  • D. Use the model for real-time predictions.
  • E. Remove records that have missing values.
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Answer: CE
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-data-ingestion https://docs.microsoft.com/en-us/azure/architecture/data-science-process/prepare-data

Question#35

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

  • A. regression
  • B. clustering
  • C. classification
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Answer: A
Regression is a supervised machine learning technique used to predict numeric values.
Reference:
https://docs.microsoft.com/en-us/learn/modules/create-regression-model-azure-machine-learning-designer/1-introduction

Question#36

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.

  • A. Python
  • B. R
  • C. C#
  • D. Scala
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Answer: AB
Use Azure Machine Learning designer for customizing using Python and R code.
Reference:
https://azure.microsoft.com/en-us/services/machine-learning/designer/#features

Question#37

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.
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Answer:
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

Question#38

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?

  • A. anomaly detection
  • B. conversational AI
  • C. computer vision
  • D. natural language processing
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Answer: C
Azure's Computer Vision service gives you access to advanced algorithms that process images and return information based on the visual features you're interested in. For example, Computer Vision can determine whether an image contains adult content, find specific brands or objects, or find human faces.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview

Question#39

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.
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Answer:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/get-started-build-detector

Question#40

In which two scenarios can you use the Form Recognizer service? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. Extract the invoice number from an invoice.
  • B. Translate a form from French to English.
  • C. Find image of product in a catalog.
  • D. Identify the retailer from a receipt.
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Answer: AD
Reference:
https://azure.microsoft.com/en-gb/services/cognitive-services/form-recognizer/#features

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