Exams / AIF-C01 / Use cases and ML techniques / Question 1
AIF-C01 practice question: Use cases and ML techniques (1 of 5)
Fundamentals of AI and ML A free question from our original AIF-C01 practice exam. Try it, then open the answer to see why each option is right or wrong.
A gym chain has membership data for 200,000 customers but no labels describing customer types. Marketing wants the data split into groups of similar customers so it can design a campaign for each group. Which machine learning approach fits?
Choose one answer.
- AA. Supervised classification trained on labelled customer types
- BB. Reinforcement learning that rewards the model for each sign-up
- CC. Regression that predicts each customer's monthly spend
- DD. Unsupervised clustering that groups customers by similarity
Show the answer and explanation
Answer: D
- A. Wrong: Classification needs labelled examples of each class. The gym has no labels, so there is nothing to train on.
- B. Wrong: Reinforcement learning learns actions through rewards in an environment. It is not used to find groups in existing records.
- C. Wrong: Regression predicts a numeric value. It does not divide customers into groups.
- D. Right: Correct. Clustering is an unsupervised technique that finds natural groups in unlabelled data.
Explanation
When data has no labels and the aim is to discover groups, the task is clustering, which is a form of unsupervised learning. Supervised learning needs labelled examples, and reinforcement learning learns from rewards for actions.
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