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Microsoft Certified: Azure AI Fundamentals
AI-900
Microsoft Azure AI Fundamentals Questions and Answers

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Viewing questions 31-40 out of questions

Questions # 31:

To complete the sentence, select the appropriate option in the answer area.

Question # 31

Options:

Answer

Answer:

Explanation

Classification

Questions # 32:

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

Question # 32

Which two fields should you use as features? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

Options:

Education Level

Last Name

Age

Income Range

First Name

Answer

A, C

Explanation

First Name, Last Name, Age and Education Level are features. Income range is a label (what you want to predict). First Name and Last Name are irrelevant in that they have no bearing on income. Age and Education level are the features you should use.

Questions # 33:

For each of the following statements, select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Question # 33

Options:

Answer

Answer:

Explanation

Clustering is a machine learning task that is used to group instances of data into clusters that contain similar characteristics. Clustering can also be used to identify relationships in a dataset

Regression is a machine learning task that is used to predict the value of the label from a set of related features.

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

Questions # 34:

To complete the sentence, select the appropriate option in the answer area.

Question # 34

Options:

Answer

Answer:

Explanation

Regression is a machine learning task that is used to predict the value of the label from a set of related features.

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

Questions # 35:

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

Options:

classification

regression

clustering

Answer

Questions # 36:

To complete the sentence, select the appropriate option in the answer area.

Question # 36

Options:

Answer

Answer:

Explanation

[Reference:, https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier, , , ]

Questions # 37:

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

Options:

to train the model twice to attain better accuracy

to train multiple models simultaneously to attain better performance

to test the model by using data that was not used to train the model

Answer

Explanation

The goal is to produce a trained (fitted) model that generalizes well to new, unknown data. The fitted model is evaluated using “new” examples from the held-out datasets (validation and test datasets) to estimate the model's accuracy in classifying new data.

https://en.wikipedia.org/wiki/Training,_validation,_and_test_sets#:~:text=Training%20dataset,- A%20training%20dataset &text=The%20goal%20is%20to%20produce,accuracy%20in%20classifying%20new%20data.

Questions # 38:

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

Options:

Azure Al Custom Vision

Azure Al Document Intelligence

Azure Al Language

Azure Al face

Answer

Explanation

Accelerate your business processes by automating information extraction. Form Recognizer applies advanced machine learning to accurately extract text, key/value pairs, and tables from documents. With just a few samples, Form Recognizer tailors its understanding to your documents, both on-premises and in the cloud. Turn forms into usable data at a fraction of the time and cost, so you can focus more time acting on the information rather than compiling it.

[Reference:, https://azure.microsoft.com/en-us/services/cognitive-services/form-recognizer/, , , , ]

Questions # 39:

You have a database that contains a list of employees and their photos.

You are tagging new photos of the employees.

For each of the following statements select Yes if the statement is true. Otherwise, select No.

NOTE: Each correct selection is worth one point.

Question # 39

Options:

Answer

Answer:

Explanation

[Reference:, https://docs.microsoft.com/en-us/azure/cognitive-services/face/overview, , https://docs.microsoft.com/en-us/azure/cognitive-services/face/concepts/face-detection, , , , ]

Questions # 40:

You need to determine the location of cars in an image so that you can estimate the distance between the cars.

Which type of computer vision should you use?

Options:

optical character recognition (OCR)

object detection

image classification

face detection

Answer

Explanation

Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.

The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like "indoor", which can't be localized with bounding boxes.

[Reference:, https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection, , , , ]

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