Amazon BDS-C00 AWS Certified Big Data – Specialty (BDS-C00) 11 24Oct2024 - Practice Quiz

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Question 1 of 30

A data scientist is tasked with developing a model to predict customer churn for a subscription-based service. They have access to historical data that includes customer demographics, usage patterns, and whether or not each customer has churned. The data scientist considers two approaches: supervised learning using a classification algorithm and unsupervised learning to identify patterns in customer behavior. Which approach would be more appropriate for predicting customer churn, and why?

Supervised learning, as it utilizes labeled data to train a model that can predict future outcomes based on historical patterns.

Unsupervised learning, since it can cluster customers into groups based on similarities without needing labeled outcomes.

Supervised learning, because it requires a large amount of data to be effective, which is not available in this case.

Unsupervised learning, as it is better suited for scenarios where the outcome is unknown and patterns need to be discovered.