최신 AI-102 Korean 무료덤프 - Microsoft Designing and Implementing a Microsoft Azure AI Solution (AI-102 Korean Version)

Explanation:

Step 1: Create a project
Create a new project.
Step 2: Upload and tag the images
Choose training images. Then upload and tag the images.
Step 3: Train the classifier model.
Train the classifier
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a- classifier

Explanation:

Explanation:

Explanation:

Explanation:
Box 1: Yes
Box 2: Yes
Box 3: No
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-detecting-faces

설명: (DumpTOP 회원만 볼 수 있음)

설명: (DumpTOP 회원만 볼 수 있음)

Explanation:

Explanation:
Box 1: "categories": ["Locations", "Persons", "Organizations"],
Locations, Persons, Organizations are in the outputs.
Scenario: Contoso plans to develop a searchable knowledgebase of all the intellectual property Note: The categories parameter is an array of categories that should be extracted. Possible category types:
"Person", "Location", "Organization", "Quantity", "Datetime", "URL", "Email". If no category is provided, all types are returned.
Box 2: {"name": " entities"}
The include wikis, so should include entities in the outputs.
Note: entities is an array of complex types that contains rich information about the entities extracted from text, with the following fields name (the actual entity name. This represents a "normalized" form) wikipediaId wikipediaLanguage wikipediaUrl (a link to Wikipedia page for the entity) etc.
Reference:
https://docs.microsoft.com/en-us/azure/search/cognitive-search-skill-entity-recognition