Free AI-102 Exam Braindumps (page: 23)

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HOTSPOT (Drag and Drop is not supported)
You develop a test method to verify the results retrieved from a call to the Computer Vision API. The call is used to analyze the existence of company logos in images. The call returns a collection of brands named brands.
You have the following code segment.
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:

  1. See Explanation section for answer.

Answer(s): A

Explanation:


Box 1: Yes
Box 2: Yes
Coordinates of a rectangle in the API refer to the top left corner.
Box 3: No


Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-brand-detection



HOTSPOT (Drag and Drop is not supported)
You develop an application that uses the Face API.
You need to add multiple images to a person group.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:


Box 1: Stream
The File.OpenRead(String) method opens an existing file for reading.
Example: Open the stream and read it back.
using (FileStream fs = File.OpenRead(path))
Box 2: CreateAsync
Create the persons for the PersonGroup. Persons are created concurrently.
Example:
await faceClient.PersonGroupPerson.CreateAsync(personGroupId, personName);


Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-add-faces



Your company uses an Azure Cognitive Services solution to detect faces in uploaded images. The method to detect the faces uses the following code.
You discover that the solution frequently fails to detect faces in blurred images and in images that contain sideways faces.
You need to increase the likelihood that the solution can detect faces in blurred images and images that contain sideways faces.
What should you do?

  1. Use a different version of the Face API.
  2. Use the Computer Vision service instead of the Face service.
  3. Use the Identify method instead of the Detect method.
  4. Change the detection model.

Answer(s): D

Explanation:

Evaluate different models.
The best way to compare the performances of the detection models is to use them on a sample dataset. We recommend calling the Face - Detect API on a variety of images, especially images of many faces or of faces that are difficult to see, using each detection model. Pay attention to the number of faces that each model returns.
The different face detection models are optimized for different tasks. See the following table for an overview of the differences.


Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/specify-detection-model



You have the following Python function for creating Azure Cognitive Services resources programmatically. def create_resource (resource_name, kind, account_tier, location) : parameters = CognitiveServicesAccount(sku=Sku(name=account_tier), kind=kind, location=location, properties={}) result = client.accounts.create(resource_group_name, resource_name, parameters)
You need to call the function to create a free Azure resource in the West US Azure region. The resource will be used to generate captions of images automatically.
Which code should you use?

  1. create_resource("res1", "ComputerVision", "F0", "westus")
  2. create_resource("res1", "CustomVision.Prediction", "F0", "westus")
  3. create_resource("res1", "ComputerVision", "S0", "westus")
  4. create_resource("res1", "CustomVision.Prediction", "S0", "westus")

Answer(s): A

Explanation:

F0 is the free tier.
Custom Vision Service
Upload images to train and customize a computer vision model for your specific use case. Once the model is trained, you can use the API to tag images using the model and evaluate the results to improve your classifier.
Incorrect:
Not C, not D: S0 is the standard tier, which isn't free.
Not A, not C: The Computer Vision service provides developers with access to advanced algorithms for processing images and returning information.
Computer Vision
Returns information about visual content found in an image:
Use tagging, descriptions, and domain-specific models to identify content and label it with confidence.
Apply adult/racy settings to enable automated restriction of adult content.
Identify image types and color schemes in pictures.


Reference:

https://docs.microsoft.com/en-us/python/api/overview/azure/cognitive-services?view=azure-python






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