Explanation:

The correct matches are based on the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore computer vision in Microsoft Azure." These materials explain that facial recognition tasks can be categorized into four major operations: verification, identification, similarity, and grouping. Each task serves a distinct purpose in facial recognition scenarios.
* Verification - "Do two images of a face belong to the same person?"The verification task determines whether two facial images represent the same individual. Azure Face API compares the facial features and returns a confidence score indicating the likelihood that the two faces belong to the same person.
* Similarity - "Does this person look like other people?"The similarity task compares a face against a collection of faces to find visually similar individuals. It does not confirm identity but measures how closely two or more faces resemble each other.
* Grouping - "Do all the faces belong together?"Grouping organizes a set of unknown faces into clusters based on similar facial features. This is used when identities are not known beforehand, helping discover potential duplicates or visually similar clusters within an image dataset.
* Identification - "Who is this person in this group of people?"The identification task is used when the system tries to determine who a specific person is by comparing their face against a known collection (face database or gallery). It returns the identity that best matches the input face.
According to Microsoft's AI-900 training, these tasks form the basis of Azure Face API's capabilities. Each helps solve a different type of facial recognition problem-from matching pairs to discovering unknown identities-making them essential components of responsible AI-based vision systems.