AWS Certified Cloud Practitioner
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A company wants to automatically label customer reviews as positive, negative, or neutral. They already have 10,000 reviews with known sentiment labels.
Which type of learning algorithm is most appropriate?
Real Exam
Community
RRitesh
A
Unsupervised Learning
B
Supervised Learning
C
Reinforcement Learning
D
Self-supervised Learning
Explanation:
Explanation
This is a Supervised Learning scenario because:
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Labeled Data: The company has 10,000 reviews with known sentiment labels (positive, negative, or neutral)
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Classification Task: The goal is to classify new reviews into predefined categories
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Training Process: The algorithm can learn from the labeled examples to predict sentiment for new, unlabeled reviews
Why Other Options Are Incorrect:
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A) Unsupervised Learning: Used when there are no labels and the algorithm must find patterns or groupings on its own
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C) Reinforcement Learning: Used for decision-making problems where an agent learns through trial and error with rewards/penalties
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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:
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Amazon Comprehend: AWS's natural language processing service that can perform sentiment analysis
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Amazon SageMaker: For building custom machine learning models for text classification
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