Practice Other Learning Paradigms (6.2.3) - Machine Learning Basics

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6 sample questions

Question 1.
What is semi-supervised learning?
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Think of the labeled data guiding the learning.
Question 2.
What does an agent learn from in reinforcement learning?
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Focus on how actions affect outcomes.
3Question 3.
What type of data does semi-supervised learning use?
- Only labeled data
- Only unlabeled data
- Both labeled and unlabeled data
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Remember the definitions of semi-supervised learning.
4Question 4.
True or False: In reinforcement learning, the agent learns without receiving any feedback.
- True
- False
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Consider how rewards influence learning.
Question 5.
Analyze a dataset where labeling new data would be costly and suggest how semi-supervised learning could improve the model's performance.
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Consider the balance of class proportions.
Question 6.
Propose methods to effectively implement reinforcement learning for a task where an agent needs to learn walking without falling.
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Think about how human learning occurs.

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