Microsoft Azure AI Fundamentals (AI-900) Practice Exam

What is Automated ML primarily designed to do?

1. Control data storage

2. Optimize budget allocations

3. Automate the iterative tasks of ML model development

4. Enhance user interface designs

The correct answer is: Automate the iterative tasks of ML model development

Automated ML (AutoML) is primarily designed to automate the iterative tasks involved in the machine learning model development process. This includes tasks such as data preprocessing, feature selection, model training, hyperparameter tuning, and evaluation. By automating these processes, AutoML allows users, even those who may not be experts in machine learning, to create and optimize machine learning models more efficiently and effectively. The main goal of AutoML is to simplify the model development workflow so that individuals can focus on interpreting results and integrating models into applications rather than spending extensive time on the technical intricacies of model building. It streamlines the entire process, enabling faster development of reliable models and making machine learning more accessible to a broader range of users and use cases. In contrast, control over data storage, optimizing budget allocations, and enhancing user interface designs are not primary functions of Automated ML. These tasks relate to different areas within data management, financial analytics, and user experience design, respectively, rather than the automated development and deployment of machine learning solutions.