2025 Realistic AI-900 Dumps are Available for Instant Access [Q40-Q61]

2025 Realistic AI-900 Dumps are Available for Instant Access

Download Exam AI-900 Practice Test Questions with 100% Verified Answers

NEW QUESTION # 40
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 # 41
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://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features

NEW QUESTION # 42
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 # 43
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:

Explanation
Graphical user interface, text, application, email Description automatically generated

NEW QUESTION # 44
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.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

NEW QUESTION # 45
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. Translate a form from French to English.
B. Extract the invoice number from an invoice.
C. Find image of product in a catalog.
D. Identity the retailer from a receipt.

Answer: B,D

Explanation:
Section: Describe features of computer vision workloads on Azure
Explanation/Reference:
https://azure.microsoft.com/en-gb/services/cognitive-services/form-recognizer/#features

NEW QUESTION # 46
You build a machine learning model by using the automated machine learning user interface (UI).
You need to ensure that the model meets the Microsoft transparency principle for responsible AI.
What should you do?

A. Set Max concurrent iterations to 0.
B. Set Validation type to Auto.
C. Set Primary metric to accuracy.
D. Enable Explain best model.

Answer: D

Explanation:
Model Explain Ability.
Most businesses run on trust and being able to open the ML "black box" helps build transparency and trust. In heavily regulated industries like healthcare and banking, it is critical to comply with regulations and best practices. One key aspect of this is understanding the relationship between input variables (features) and model output. Knowing both the magnitude and direction of the impact each feature (feature importance) has on the predicted value helps better understand and explain the model. With model explain ability, we enable you to understand feature importance as part of automated ML runs.
Reference:
https://azure.microsoft.com/en-us/blog/new-automated-machine-learning-capabilities-in-azure-machine-learning

NEW QUESTION # 47
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://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features

NEW QUESTION # 48
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-us/azure/cognitive-services/text-analytics/overview

NEW QUESTION # 49
You are developing a model to predict events by using classification.
You have a confusion matrix for the model scored on test data as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 50
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-science-process/create-features

NEW QUESTION # 51
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation

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

NEW QUESTION # 52
Match the types of computer vision 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/face/
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection

NEW QUESTION # 53
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:
Explanation
Graphical user interface, text, application, email Description automatically generated

The translator service provides multi-language support for text translation, transliteration, language detection, and dictionaries.
Speech-to-Text, also known as automatic speech recognition (ASR), is a feature of Speech Services that provides transcription.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/Translator/translator-info-overview
https://docs.microsoft.com/en-us/legal/cognitive-services/speech-service/speech-to-text/transparency-note

NEW QUESTION # 54
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?

A. entity recognition
B. language detection
C. key phrase extraction
D. sentiment analysis

Answer: C

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 # 55
You plan to apply Text Analytics API features to a technical support ticketing system.
Match the Text Analytics API features to the appropriate natural language processing scenarios.
To answer, drag the appropriate feature from the column on the left to its scenario on the right. Each feature may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation

Box1: Sentiment analysis
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
Box 2: Broad entity extraction
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.
Box 3: Entity Recognition
Named Entity Recognition: Identify and categorize entities in your text as people, places, organizations, date/time, quantities, percentages, currencies, and more. Well-known entities are also recognized and linked to more information on the web.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing
https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics

NEW QUESTION # 56
You need to reduce the load on telephone operators by implementing a chatbot to answer simple questions with predefined answers.
Which two AI service should you use to achieve the goal? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A. Translator Text
B. Text Analytics
C. Azure Bot Service
D. QnA Maker

Answer: C,D

Explanation:
Section: Describe features of conversational AI workloads on Azure
Explanation:
Bots are a popular way to provide support through multiple communication channels. You can use the QnA Maker service and Azure Bot Service to create a bot that answers user questions.
Reference:
https://docs.microsoft.com/en-us/learn/modules/build-faq-chatbot-qna-maker-azure-bot-service/

NEW QUESTION # 57
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 # 58
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:

NEW QUESTION # 59
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

NEW QUESTION # 60
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation

Reference:
https://azure.microsoft.com/en-gb/services/cognitive-services/speech-to-text/#features Speech recognition means Speech to Text. In the above example as a person speaks the words are converted into text of the same language. Hence Speech to Text also called Speech recognition is the right answer.
Speech recognition - the ability to detect and interpret spoken input.
Speech synthesis - the ability to generate spoken output.
https://docs.microsoft.com/en-us/learn/modules/recognize-synthesize-speech/1-introduction