Azure Data Scientists Associate Practice Exam

What is the first step in creating an image classification labeling project in Azure ML studio?

1. Choose multi-class as the labeling task type

2. Select the image type for analysis

3. Upload images to the workspace

4. Assign labels to the images directly

The correct answer is: Choose multi-class as the labeling task type

Choosing multi-class as the labeling task type is indeed a foundational step when creating an image classification labeling project in Azure ML Studio. This step establishes the framework for how the data will be categorized and classified throughout the project. Image classification typically involves assigning one of several labels to an image, and specifying that the task is multi-class informs the system that it should expect multiple classes to choose from for each image. Selecting the image type for analysis is also an important aspect, but it typically comes after deciding on the labeling task type. Determining the task type clearly sets the stage for the subsequent steps regarding how images will be processed and analyzed. Uploading images to the workspace is a necessary component of the project setup, but it is intended to follow the initial setup and configuration of the task parameters. Without clarifying the task type first, uploading images would not be as effectively directed toward the classification goals. Assigning labels directly to the images is typically one of the last steps in the process. It comes after establishing the type of labeling task, selecting the appropriate image type, and uploading the relevant data to the workspace. Having a defined task type helps ensure that the labeling process is systematic and aligns with the intended outcomes for model training and evaluation. Thus, starting with the