Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module "Describe features of common AI workloads", there are three primary supervised and unsupervised machine learning types: Regression, Classification, and Clustering. Each type of learning addresses a different kind of problem depending on the data and desired prediction output.
* Regression - Regression models are used to predict numeric, continuous values. The study guide specifies that "regression predicts a number." In the scenario "Predict how many minutes late a flight will arrive based on the amount of snowfall," the output (minutes late) is a continuous numeric value.
Therefore, this is a regression problem. Regression algorithms like linear regression or decision tree regression estimate relationships between variables and predict measurable quantities.
* Clustering - Clustering falls under unsupervised learning, where the model identifies natural groupings or patterns in unlabeled data. The official AI-900 training material states that "clustering is used to find groups or segments of data that share similar characteristics." The scenario "Segment customers into different groups to support a marketing department" fits this description because the goal is to group customers based on behavior or demographics without predefined labels. Thus, it is a clustering problem.
* Classification - Classification is a supervised learning method used to predict discrete categories or labels. The AI-900 content defines classification as "predicting which category an item belongs to." The scenario "Predict whether a student will complete a university course" requires a yes/no (binary) outcome, which is a classic classification problem. Examples include logistic regression, decision trees, or neural networks trained for categorical prediction.
In summary:
* Regression # Predicts continuous numeric outcomes.
* Clustering # Groups data by similarities without predefined labels.
* Classification # Predicts discrete or categorical outcomes.
Hence, the correct and verified mappings based on the official AI-900 study material are:
* Regression # Flight delay prediction
* Clustering # Customer segmentation
* Classification # Course completion prediction