Explanation

This is a Supervised Learning scenario because:

• Labeled Data: The company has 10,000 reviews with known sentiment labels (positive, negative, or neutral)
• Classification Task: The goal is to classify new reviews into predefined categories
• Training Process: The algorithm can learn from the labeled examples to predict sentiment for new, unlabeled reviews

Why Other Options Are Incorrect:

• A) Unsupervised Learning: Used when there are no labels and the algorithm must find patterns or groupings on its own
• C) Reinforcement Learning: Used for decision-making problems where an agent learns through trial and error with rewards/penalties
• D) Self-supervised Learning: A subset of unsupervised learning where the model generates its own labels from the data structure

Key AWS Service for This Use Case:

• Amazon Comprehend: AWS's natural language processing service that can perform sentiment analysis
• Amazon SageMaker: For building custom machine learning models for text classification