Microsoft Azure AI Fundamentals (AI-900) Practice Exam 2025 – Complete Study Guide

In computer vision, tasks can vary widely, and predicting travel methods based on distance falls under the category of classification. This type of task involves assigning a label or category to an input based on its features. In this specific case, the system analyzes the distance information and then classifies the potential travel methods that could be used, such as walking, biking, driving, or taking public transportation.

Classification utilizes training data where the distances are associated with specific travel methods, allowing the model to learn patterns and relationships. After training, when given a new distance, the model can predict the most likely travel method by applying the learned associations.

Other options, such as grouping, facial recognition, and object detection, do not pertain to predicting travel methods based on distance. Grouping generally refers to clustering data points together based on similarity, while facial recognition specifically identifies individuals based on facial features. Object detection is focused on locating and classifying objects within images rather than predicting choices based on distance. Thus, classification is the most suitable task for this scenario.