Microsoft AI900 Exam Dumps|QAs Page – 2

Microsoft AI900 Exam Dumps post contains real and latest questions for Microsoft Azure Fundamentals.

Microsoft AI900 Exam Dumps – QAs 26-50

Q26. You are building an AI-based app.
You need to ensure that the app uses the principles for responsible AI.
Which two principles should you follow? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

1. Implement an Agile software development methodology
2. Implement a process of AI model validation as part of the software review process
3. Establish a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy officer
4. Prevent the disclosure of the use of AI-based algorithms for automated decision making

Q27. You need to predict the sea level in meters for the next 10 years.
Which type of machine learning should you use?

1. classification
2. regression
3. clustering

Q28. 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.
Hot Area:

Correct answer

Reference:
https://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features

Q29. You are evaluating whether to use a basic workspace or an enterprise workspace in Azure Machine Learning.
What are two tasks that require an enterprise workspace? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

1. Use a graphical user interface (GUI) to run automated machine learning experiments.
2. Create a compute instance to use as a workstation.
3. Use a graphical user interface (GUI) to define and run machine learning experiments from Azure Machine Learning designer.
4. Create a dataset from a comma-separated value (CSV) file.

Q30. You need to predict the income range of a given customer by using the following dataset.

Which two fields should you use as features? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

1. Education Level
2. Last Name
3. Age
4. Income Range
5. First Name

Q31. HOTSPOT –
To complete the sentence, select the appropriate option in the answer area.
Hot Area:

Correct answer

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer#deploy

Q32. 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?

1. fairness
2. inclusiveness
3. reliability and safety
4. accountability

Q33. You have the Predicted vs. True chart shown in the following exhibit.

Which type of model is the chart used to evaluate?

1. classification
2. regression
3. clustering

Q34. Which type of machine learning should you use to predict the number of gift cards that will be sold next month?

1. classification
2. regression
3. clustering

Q35. HOTSPOT –
To complete the sentence, select the appropriate option in the answer area.
Hot Area:

Correct answer

Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai

Q36. HOTSPOT –
Select the answer that correctly completes the sentence.
Hot Area:

Correct answer

Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai

Q37. HOTSPOT –
To complete the sentence, select the appropriate option in the answer area.
Hot Area:

Correct answer

Q38. 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.
Hot Area:

Correct answer

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance

Q39. You are building a tool that will process images from retail stores and identify the products of competitors.
The solution will use a custom model.
Which Azure Cognitive Services service should you use?

1. Custom Vision
2. Form Recognizer
3. Face
4. Computer Vision

Q40. 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.
Hot Area:

Correct answer

Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks

Q41. 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.
Hot Area:

Correct answer

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer

Q42. You have a dataset that contains information about taxi journeys that occurred during a given period.
You need to train a model to predict the fare of a taxi journey.
What should you use as a feature?

1. the number of taxi journeys in the dataset
2. the trip distance of individual taxi journeys
3. the fare of individual taxi journeys
4. the trip ID of individual taxi journeys

Q43. 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.
Select and Place:

Correct answer

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

Q44. Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?

1. Form Recognizer
2. Text Analytics
3. Language Understanding
4. Custom Vision

Q45. 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.
Hot Area:

Correct answer

Q46. HOTSPOT –
You have the following dataset.

You plan to use the dataset to train a model that will predict the house price categories of houses.
What are Household Income and House Price Category? To answer, select the appropriate option in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

Correct answer

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/interpret-model-results

Q47. HOTSPOT –
To complete the sentence, select the appropriate option in the answer area.
Hot Area:

Correct answer

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/concept-designer

Q48. 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.
Hot Area:

Correct answer

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-designer-python
https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml

Q49. A medical research project uses a large anonymized dataset of brain scan images that are categorized into predefined brain haemorrhage types.
You need to use machine learning to support early detection of the different brain haemorrhage types in the images before the images are reviewed by a person.
This is an example of which type of machine learning?

1. clustering
2. regression
3. classification

Q50. When training a model, why should you randomly split the rows into separate subsets?

1. to train the model twice to attain better accuracy
2. to train multiple models simultaneously to attain better performance
3. to test the model by using data that was not used to train the model