FREE PDF MICROSOFT - AI-900 - ACCURATE MICROSOFT AZURE AI FUNDAMENTALS EXAMCOLLECTION

Free PDF Microsoft - AI-900 - Accurate Microsoft Azure AI Fundamentals Examcollection

Free PDF Microsoft - AI-900 - Accurate Microsoft Azure AI Fundamentals Examcollection

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Microsoft Azure AI Fundamentals Sample Questions (Q164-Q169):

NEW QUESTION # 164
You have the Predicted vs. True chart shown in the following exhibit.

Which type of model is the chart used to evaluate?

  • A. classification
  • B. regression
  • C. clustering

Answer: B

Explanation:
Explanation
What is a Predicted vs. True chart?
Predicted vs. True shows the relationship between a predicted value and its correlating true value for a regression problem. This graph can be used to measure performance of a model as the closer to the y=x line the predicted values are, the better the accuracy of a predictive model.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-m


NEW QUESTION # 165
You need to provide content for a business chatbot that will help answer simple user queries.
What are three ways to create question and answer text by using QnA Maker? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. Import chit-chat content from a predefined data source.
  • B. Use automated machine learning to train a model based on a file that contains the questions.
  • C. Generate the questions and answers from an existing webpage.
  • D. Manually enter the questions and answers.
  • E. Connect the bot to the Cortana channel and ask questions by using Cortana.

Answer: A,C,D

Explanation:
Explanation
Automatic extraction
Extract question-answer pairs from semi-structured content, including FAQ pages, support websites, excel files, SharePoint documents, product manuals and policies.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/content-types


NEW QUESTION # 166
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.

Answer:

Explanation:

Reference:
https://developers.google.com/machine-learning/practica/image-classification
https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/object-detection-model-builder
https://nanonets.com/blog/how-to-do-semantic-segmentation-using-deep-learning/


NEW QUESTION # 167
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.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles


NEW QUESTION # 168
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks


NEW QUESTION # 169
......

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