Google CloudFundamentals of Generative AI

Supervised Learning & ML Concepts — Google Gen AI Leader Practice Question

A representative Google Cloud Generative AI Leader (Google Gen AI Leader) exam question on Supervised Learning & ML Concepts. Work through it below, then read why each option is right or wrong.

Short answer

The correct answer is B. Supervised learning, because the model can learn from labeled examples of churned and non-churned customers.

Supervised learning is the correct approach because the company has labeled data (customers marked as churned or not churned) and wants to predict a specific outcome. The model learns the mapping from input features to known labels. Unsupervised learning would be inappropriate here because it is used when labels are not available, such as for clustering or anomaly detection without predefined categories.

The Question

A retail company wants to build a model that predicts whether a customer will churn based on historical purchase data, customer demographics, and past churn labels. The data science team has a large labeled dataset available. Which type of machine learning approach is most appropriate for this use case?

AReinforcement learning, because the model needs to optimize a reward signal based on customer retention
BSupervised learning, because the model can learn from labeled examples of churned and non-churned customersCorrect
CGenerative AI, because the model needs to generate predictions about future customer behavior
DUnsupervised learning, because the model needs to discover hidden patterns in customer behavior

Why B is correct

Supervised learning is the correct approach because the company has labeled data (customers marked as churned or not churned) and wants to predict a specific outcome. The model learns the mapping from input features to known labels. Unsupervised learning would be inappropriate here because it is used when labels are not available, such as for clustering or anomaly detection without predefined categories.

Why the other options are wrong

Option A: Reinforcement learning, because the model needs to optimize a reward signal based on customer retention

Option A does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (B) is the only one that fully meets every constraint stated in the question.

Option C: Generative AI, because the model needs to generate predictions about future customer behavior

Option C does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (B) is the only one that fully meets every constraint stated in the question.

Option D: Unsupervised learning, because the model needs to discover hidden patterns in customer behavior

Option D does not satisfy the requirement in the scenario. Review the explanation above: the correct choice (B) is the only one that fully meets every constraint stated in the question.

Key idea: Supervised Learning & ML Concepts

Supervised learning is the correct approach because the company has labeled data (customers marked as churned or not churned) and wants to predict a specific outcome. The model learns the mapping from input features to known labels. Unsupervised learning would be inappropriate here because it is used when labels are not available, such as for clustering or anomaly detection without predefined categories. On the Google Gen AI Leader exam, questions in the "Fundamentals of Generative AI" domain test whether you can map a scenario's constraints to the right choice. Read the requirement carefully, eliminate options that violate any single constraint, and pick the one that satisfies all of them with the least operational overhead.

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