Microsoft AI-900 PDF Questions - Increase Your Exam Passing Chances
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The AI-900 Exam covers a wide range of topics related to AI and ML such as Understanding AI workloads and considerations, Understanding fundamental principles of machine learning on Azure, Understanding features of computer vision workloads on Azure, Understanding features of Natural Language Processing (NLP) workloads on Azure, Understanding features of conversational AI workloads on Azure, and many more.
Microsoft Azure AI Fundamentals Sample Questions (Q279-Q284):
NEW QUESTION # 279
Match the Al solution to the appropriate task.
To answer, drag the appropriate solution from the column on the left to its task on the right. Each solution may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
NEW QUESTION # 280
Select the answer that correctly completes the sentence
Answer:
Explanation:
NEW QUESTION # 281
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://www.cloudfactory.com/data-labeling-guide
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
NEW QUESTION # 282
You are developing a solution that uses the Text Analytics service.
You need to identify the main talking points in a collection of documents.
Which type of natural language processing should you use?
Answer: A
Explanation:
Explanation
Broad entity extraction: Identify important concepts in text, including key Key phrase extraction/ Broad entity extraction: Identify important concepts in text, including key phrases and named entities such as people, places, and organizations.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing
NEW QUESTION # 283
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Explanation
Reliability and safety: To build trust, it's critical that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions. These systems should be able to operate as they were originally designed, respond safely to unanticipated conditions, and resist harmful manipulation.
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles AI systems should perform reliably and safely. For example, consider an AI-based software system for an autonomous vehicle; or a machine learning model that diagnoses patient symptoms and recommends prescriptions. Unreliability in these kinds of system can result in substantial risk to human life.
https://docs.microsoft.com/en-us/learn/modules/get-started-ai-fundamentals/7-understand-responsible-ai
NEW QUESTION # 284
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