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Microsoft AI-900 Mock Exams & Free AI-900 Updates
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Microsoft AI-900 exam, also known as the Microsoft Azure AI Fundamentals exam, is a certification exam designed for individuals who want to demonstrate their foundational knowledge of artificial intelligence and its applications in Microsoft Azure. AI-900 exam validates the candidates' ability to identify the fundamental concepts of AI, machine learning, and data analytics. It also tests their understanding of how to apply these concepts to Azure services.
Passing the AI-900 Exam is beneficial for individuals who are looking to start a career in AI and machine learning, or those who want to demonstrate their knowledge and expertise in these areas. Microsoft Azure AI Fundamentals certification can be useful for IT professionals, developers, data scientists, business analysts, and other professionals who want to explore the potential of AI and machine learning in their respective fields.
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Microsoft AI-900 Certification Exam is an excellent starting point for individuals who are interested in pursuing a career in AI or who want to demonstrate their expertise in the field. It covers a wide range of topics related to AI and the Azure platform and provides a valuable credential that can help individuals stand out in the job market.
Microsoft Azure AI Fundamentals Sample Questions (Q210-Q215):
NEW QUESTION # 210
Match the types of natural languages processing 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.
Answer:
Explanation:
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics
NEW QUESTION # 211
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://docs.microsoft.com/en-gb/azure/cognitive-services/qnamaker/concepts/data-sources-and-content
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/choose-natural-language-processing-service QnA maker conversational AI service and has nothing to do with SQL database You can easily create a user support bot solution on Microsoft Azure using a combination of two core technologies:
- QnA Maker. This cognitive service enables you to create and publish a knowledge base with built-in natural language processing capabilities.
- Azure Bot Service. This service provides a framework for developing, publishing, and managing bots on Azure.
https://docs.microsoft.com/en-us/learn/modules/build-faq-chatbot-qna-maker-azure-bot-service/2-get-started-qna-bot LUIS is used to understand user intent from utterances.
Creating a language understanding application with Language Understanding consists of two main tasks. First you must define entities, intents, and utterances with which to train the language model - referred to as authoring the model. Then you must publish the model so that client applications can use it for intent and entity prediction based on user input.
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/choose-natural-language-processing-service
NEW QUESTION # 212
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 # 213
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 214
Match the facial recognition tasks to the appropriate questions.
To answer, drag the appropriate task from the column on the left to its question on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: verification
Face verification: Check the likelihood that two faces belong to the same person and receive a confidence score.
Box 2: similarity
Box 3: Grouping
Box 4: identification
Face detection: Detect one or more human faces along with attributes such as: age, emotion, pose, smile, and facial hair, including 27 landmarks for each face in the image.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/face/#features
NEW QUESTION # 215
......
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