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AI-900 Dumps
Microsoft Azure AI Fundamentals (beta)
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100% Valid and Newest Version AI-900 Questions & Answers shared by Certleader
https://www.certleader.com/AI-900-dumps.html (155 Q&As)
NEW QUESTION 1
- (Exam Topic 1)
You are designing an AI system that empowers everyone, including people who have hearing, visual, and other impairments.
This is an example of which Microsoft guiding principle for responsible AI?
A. fairness
B. inclusiveness
C. reliability and safety
D. accountability
Answer: B
Explanation:
Inclusiveness: At Microsoft, we firmly believe everyone should benefit from intelligent technology, meaning it must incorporate and address a broad range of
human needs and experiences. For the 1 billion people with disabilities around the world, AI technologies can be a game-changer.
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles
NEW QUESTION 2
- (Exam Topic 1)
You are building an AI system.
Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?
A. Ensure that all visuals have an associated text that can be read by a screen reader.
B. Enable autoscaling to ensure that a service scales based on demand.
C. Provide documentation to help developers debug code.
D. Ensure that a training dataset is representative of the population.
Answer: C
Explanation:
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles
NEW QUESTION 3
- (Exam Topic 1)
A company employs a team of customer service agents to provide telephone and email support to customers. The company develops a webchat bot to provide
automated answers to common customer queries.
Which business benefit should the company expect as a result of creating the webchat bot solution?
A. increased sales
B. a reduced workload for the customer service agents
C. improved product reliability
Answer: B
NEW QUESTION 4
- (Exam Topic 1)
To complete the sentence, select the appropriate option in the answer area.
A. Mastered
B. Not Mastered
Answer: A
Explanation:
Privacy and security.
As AI becomes more prevalent, protecting privacy and securing important personal and business information is becoming more critical and complex. With AI,
privacy and data security issues require especially close attention because access to data is essential for AI systems to make accurate and informed predictions
and decisions about people. AI systems must comply with privacy laws that require transparency about the collection, use, and storage of data and mandate that
consumers have appropriate controls to choose how their data is used. At Microsoft, we are continuing to research privacy and security breakthroughs (see next
unit) and invest in robust compliance processes to ensure that data collected and used by our AI systems is handled responsibly.
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100% Valid and Newest Version AI-900 Questions & Answers shared by Certleader
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Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles
NEW QUESTION 5
- (Exam Topic 1)
Your company is exploring the use of voice recognition technologies in its smart home devices. The company wants to identify any barriers that might
unintentionally leave out specific user groups.
This an example of which Microsoft guiding principle for responsible AI?
A. accountability
B. fairness
C. inclusiveness
D. privacy and security
Answer: C
Explanation:
Reference:
https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles
NEW QUESTION 6
- (Exam Topic 1)
To complete the sentence, select the appropriate option in the answer area.
A. Mastered
B. Not Mastered
Answer: A
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection
NEW QUESTION 7
- (Exam Topic 1)
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.
A. Mastered
B. Not Mastered
Answer: A
Explanation:
Reference:
https://docs.microsoft.com/en-us/learn/paths/get-started-with-artificial-intelligence-on-azure/
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100% Valid and Newest Version AI-900 Questions & Answers shared by Certleader
https://www.certleader.com/AI-900-dumps.html (155 Q&As)
NEW QUESTION 8
- (Exam Topic 2)
Which metric can you use to evaluate a classification model?
A. true positive rate
B. mean absolute error (MAE)
C. coefficient of determination (R2)
D. root mean squared error (RMSE)
Answer: A
Explanation:
What does a good model look like?
An ROC curve that approaches the top left corner with 100% true positive rate and 0% false positive rate will be the best model. A random model would display as
a flat line from the bottom left to the top right corner. Worse than random would dip below the y=x line.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-ml#classification
NEW QUESTION 9
- (Exam Topic 2)
To complete the sentence, select the appropriate option in the answer area.
A. Mastered
B. Not Mastered
Answer: A
Explanation:
In machine learning, if you have labeled data, that means your data is marked up, or annotated, to show the target, which is the answer you want your machine
learning model to predict.
In general, data labeling can refer to tasks that include data tagging, annotation, classification, moderation, transcription, or processing.
Reference:
https://www.cloudfactory.com/data-labeling-guide
NEW QUESTION 10
- (Exam Topic 2)
Which type of machine learning should you use to predict the number of gift cards that will be sold next month?
A. classification
B. regression
C. clustering
Answer: C
Explanation:
Clustering, in machine learning, is a method of grouping data points into similar clusters. It is also called segmentation.
Over the years, many clustering algorithms have been developed. Almost all clustering algorithms use the features of individual items to find similar items. For
example, you might apply clustering to find similar people by demographics. You might use clustering with text analysis to group sentences with similar topics or
sentiment.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/machine-learning-initialize-m
NEW QUESTION 10
......
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100% Valid and Newest Version AI-900 Questions & Answers shared by Certleader
https://www.certleader.com/AI-900-dumps.html (155 Q&As)
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