Microsoft Azure AI Fundamentals AI-900 Practice Question

Automated model selection and hyperparameter tuning - This is the correct answer. Azure's automated machine learning feature includes automated model selection and hyperparameter tuning, which automatically selects the best algorithm for your predictive model and optimizes hyperparameters. This streamlines the model development process and helps improve the model's performance.

Automated feature engineering to create new features from existing data - While automated feature engineering is helpful for transforming raw data into meaningful features, it does not directly involve selecting the best algorithm or tuning hyperparameters, which are the focus of the question.

Deployment of models as scalable web services - Deployment helps you make your model available for real-time or batch predictions, but it does not focus on the algorithm selection or hyperparameter tuning during the model development phase.

Visualization of data using interactive dashboards - Visualization is a key part of understanding data and model performance, but it does not directly contribute to selecting algorithms or tuning hyperparameters for the predictive model.