Which methodology should the company use to meet these requirements?

A company has petabytes of unlabeled customer data to use for an advertisement campaign. The

company wants to classify its customers into tiers to advertise and promote the company’s products.

Which methodology should the company use to meet these requirements?
A . Supervised learning
B . Unsupervised learning
C . Reinforcement learning
D . Reinforcement learning from human feedback (RLHF)

View Answer

Answer: B

Explanation: Unsupervised learning is used when working with unlabeled data, such as the customer data described in this scenario. This methodology allows the company to identify patterns and group similar customers into clusters or tiers without the need for predefined labels. Techniques like clustering (e.g., K-Means or hierarchical clustering) would help classify customers based on shared characteristics for targeted advertisement campaigns. Why not the other options? A: Supervised learning: Supervised learning requires labeled data, which is not available in this case. Labels would need to be provided for each customer, making this approach unsuitable for the given scenario.