Recall & Review
beginner
What is data privacy in machine learning?
Data privacy means protecting personal or sensitive information used in machine learning so it is not exposed or misused.
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beginner
Why is privacy important when training machine learning models?
Privacy is important to keep individuals' data safe, avoid legal issues, and build trust with users.
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intermediate
What is differential privacy?
Differential privacy is a technique that adds noise to data or results to protect individual information while still allowing useful analysis.
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beginner
Name one common risk to privacy in machine learning.
One common risk is data leakage, where sensitive information can be unintentionally revealed through model outputs or training data exposure.
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beginner
How can anonymization help with privacy?
Anonymization removes or masks personal identifiers in data so individuals cannot be easily recognized.
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What does differential privacy do to protect data?
✗ Incorrect
Differential privacy adds noise to data or outputs to hide individual details while keeping overall patterns.
Which of these is a privacy risk in machine learning?
✗ Incorrect
Data leakage can expose sensitive information unintentionally.
Why should personal data be anonymized before training?
✗ Incorrect
Anonymization helps protect privacy by removing personal identifiers.
Which law often requires privacy protection for personal data?
✗ Incorrect
GDPR is a law that protects personal data privacy.
What is a simple way to protect privacy in datasets?
✗ Incorrect
Removing names and IDs helps keep data anonymous.
Explain why privacy is important in machine learning and name two ways to protect it.
Think about protecting personal data and techniques to keep it safe.
You got /3 concepts.
Describe what data leakage is and how it can affect privacy in machine learning.
Consider how sensitive info might be revealed unintentionally.
You got /3 concepts.