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 analyze past customer behavior to predict what products a user might buy next.
They use historical data with labels such as previous purchases, ratings, or clicks to train the model.
This approach falls under Supervised Learning, where the model learns from input-output pairs.
Unsupervised Learning is used when there are no labels, such as grouping similar users without predefined categories.
Reinforcement Learning is about learning through rewards and penalties, mostly used in robotics or game AI.
Natural Language Processing focuses on understanding human language, which is different from predicting purchase behavior.
Therefore, predicting customer preferences in e-commerce through recommendation systems is typically a Supervised Learning application.