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Questions and Answers
Which type of machine learning technique does not require labeled data?
Which type of machine learning technique does not require labeled data?
- Reinforcement learning
- Deep learning
- Supervised learning
- Unsupervised learning (correct)
What is the goal of unsupervised learning?
What is the goal of unsupervised learning?
- To train models using labeled data
- To predict future outcomes based on past data
- To classify data into different categories
- To find the hidden patterns and insights from the given data (correct)
Can unsupervised learning be directly applied to regression or classification problems?
Can unsupervised learning be directly applied to regression or classification problems?
- Yes, because it finds hidden patterns
- Yes, because it uses input data
- No, because it requires labeled data (correct)
- No, because it is not accurate
How does unsupervised learning compare to learning in the human brain?
How does unsupervised learning compare to learning in the human brain?
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What type of learning is suitable for cases where labeled data is not available?
What type of learning is suitable for cases where labeled data is not available?
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Study Notes
Unsupervised Learning
- Unsupervised learning is a type of machine learning technique that does not require labeled data.
- The primary goal of unsupervised learning is to discover patterns, relationships, or structures within the data.
- Unsupervised learning cannot be directly applied to regression or classification problems because it does not use labeled data to train models.
- Unsupervised learning is similar to how humans learn in the sense that our brains also identify patterns and relationships without prior knowledge or labels.
- Unsupervised learning is suitable for cases where labeled data is not available or is scarce.
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Description
Test your knowledge on unsupervised machine learning techniques and learn how to find hidden patterns in datasets without labeled data. Explore clustering algorithms, dimensionality reduction, and anomaly detection methods.
