Microsoft Azure AI Fundamentals AI-900 Practice Question

Discovering customer segments with similar purchasing behaviors for marketing purposes - This is the correct answer. The scenario where a machine learning technique finds patterns in data without relying on labeled outcomes is best addressed by clustering. In this case, the goal is to segment customers based on their purchasing behaviors, which is an unsupervised learning task that does not require labeled data.

Predicting housing prices based on features like size and location - This task typically requires supervised learning, where the model learns from labeled data, for example, by using historical housing prices to make predictions on new data.

Determining if a transaction is fraudulent based on past labeled data - Fraud detection is a supervised learning task where labeled data (fraudulent vs. legitimate transactions) is used to train a model to classify future transactions.

Forecasting future stock prices based on historical data - While stock price forecasting may involve time series analysis, it is also typically a supervised learning task that uses historical data with known outcomes to predict future trends.