Question

A website selling products uses recommendation engines to predict what products a customer is likely to purchase. This functionality is achieved through:

• A. Supervised Learning
• B. Unsupervised Learning
• C. Reinforcement Learning
• D. Natural Language Processing

Hint:

Recommendation engines = Supervised Learning using labeled historical data.

Answer 1

The Correct Option is A

Recommendation engines forecast future product interest by examining past customer actions.
These systems train models using historical data, including past purchases, ratings, and clicks.
This methodology is classified as Supervised Learning, involving learning from labeled input-output examples.
Unsupervised Learning is applied when data lacks labels, for instance, in clustering users with similar characteristics without pre-existing groups.
Reinforcement Learning, primarily utilized in robotics and game AI, operates based on rewards and penalties.
Natural Language Processing, focused on comprehending human language, is distinct from predicting purchase behavior.
Consequently, forecasting e-commerce customer preferences via recommendation systems typically constitutes a Supervised Learning task.