Microsoft Azure AI Fundamentals (AI-900) Practice Exam

What feature does Automated ML provide for training pipelines?

1. The ability to use custom Python scripts

2. Exclusive use of predefined models

3. The ability to connect to external databases

4. The capability to generate reports automatically

The correct answer is: The ability to use custom Python scripts

Automated Machine Learning (AutoML) in Microsoft Azure provides the ability to use custom Python scripts as a key feature for training pipelines. This capability allows data scientists and developers to leverage their existing knowledge and tools while also benefiting from the automation provided by AutoML. By integrating custom scripts, users can tailor the training process to their specific needs, optimize models with unique algorithms, or incorporate domain-specific logic that goes beyond the preset capabilities of the Automated ML service. In contrast, relying exclusively on predefined models lacks the flexibility needed for custom solutions and would limit the user's ability to innovate or refine the learning process beyond the provided options. While connecting to external databases can be essential for data ingestion and management, it does not directly relate to the actual training of the models within an Automated ML pipeline. Similarly, the generation of reports, while potentially useful for monitoring and evaluating models, is not a primary feature focused on the training aspect itself.