Exam Code: AI-900 (Practice Exam Latest Test Questions VCE PDF)
Exam Name: Microsoft Azure AI Fundamentals (beta)
Certification Provider: Microsoft
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NEW QUESTION 1
HOTSPOT
Select the answer that correctly completes the sentence.
Solution:
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 2
You use Azure Machine Learning designer to publish an inference pipeline.
Which two parameters should you use to consume the pipeline? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. the model name
- B. the training endpoint
- C. the authentication key
- D. the REST endpoint
Answer: CD
Explanation:
https://docs.microsoft.com/en-in/learn/modules/create-regression-model-azure-machine-learning-designer/deploy-service
NEW QUESTION 3
DRAG DROP
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.
Solution:
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.
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 4
DRAG DROP
Match the Azure Cognitive Services service to the appropriate actions.
To answer, drag the appropriate service from the column on the left to its action on the right. Each service may he used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Solution:
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 5
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.
Solution:
Box 1: Yes
Azure bot service can be integrated with the powerful AI capabilities with Azure Cognitive Services.
Box 2: Yes
Azure bot service engages with customers in a conversational manner.
Box 3: No
The QnA Maker service creates knowledge base, not question and answers sets.
Note: You can use the QnA Maker service and a knowledge base to add question-and- answer support to your bot. When you create your knowledge base, you seed it with questions and answers.
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 6
For which two workloads can you use computer vision? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.
- A. creating photorealistic images by using three-dimensional models
- B. assigning the color pixels in an image to object names
- C. describing the contents of an image
- D. detecting inconsistencies and anomalies in a stream of data
- E. creating visual representations of numerical data
Answer: BC
NEW QUESTION 7
When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable.
This is an example of which Microsoft guiding principle for responsible AI?
- A. transparency
- B. inclusiveness
- C. fairness
- D. privacy and security
Answer: A
Explanation:
Achieving transparency helps the team to understand the data and algorithms used to train the model, what transformation logic was applied to the data, the final model generated, and its associated assets. This information offers insights about how the model was created, which allows it to be reproduced in a transparent way.
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best- practices/trusted-ai
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai
NEW QUESTION 8
DRAG DROP
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.
Solution:
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 9
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.
Solution:
Box 1: Yes
Automated machine learning, also referred to as automated ML or AutoML, is the process
of automating the time consuming, iterative tasks of machine learning model development. It allows data scientists, analysts, and developers to build ML models with high scale, efficiency, and productivity all while sustaining model quality.
Box 2: No
Box 3: Yes
During training, Azure Machine Learning creates a number of pipelines in parallel that try different algorithms and parameters for you. The service iterates through ML algorithms paired with feature selections, where each iteration produces a model with a training score. The higher the score, the better the model is considered to "fit" your data. It will stop once it hits the exit criteria defined in the experiment.
Box 4: No
Apply automated ML when you want Azure Machine Learning to train and tune a model for you using the target metric you specify.
The label is the column you want to predict.
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 10
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.
Solution:
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 11
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.
Solution:
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 12
HOTSPOT
To complete the sentence, select the appropriate option in the answer area.
Solution:
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 13
You need to build an app that will read recipe instructions aloud to support users who have reduced vision.
Which version service should you use?
- A. Text Analytics
- B. Translator Text
- C. Speech
- D. Language Understanding (LUIS)
Answer: C
Explanation:
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/text-to-speech/#features
NEW QUESTION 14
Which AI service can you use to interpret the meaning of a user input such as “Call me back later?”
- A. Translator Text
- B. Text Analytics
- C. Speech
- D. Language Understanding (LUIS)
Answer: D
Explanation:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis
NEW QUESTION 15
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.
Solution:
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 16
DRAG DROP
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.
Solution:
Box 1: Entity recognition
Classify a broad range of entities in text, such as people, places, organisations, date/time and percentages, using named entity recognition. Whereas:- Get a list of relevant phrases that best describe the subject of each record using key phrase extraction.
Box 2: Sentiment analysis
Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.
Box 3: Translation
Using Microsoft’s Translator text API
This versatile API from Microsoft can be used for the following: Translate text from one language to another.
Transliterate text from one script to another. Detecting language of the input text.
Find alternate translations to specific text. Determine the sentence length.
Does this meet the goal?
- A. Yes
- B. Not Mastered
Answer: A
NEW QUESTION 17
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