Practice Differential Privacy (dp) (13.2) - Privacy-Aware and Robust Machine Learning
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Differential Privacy (DP)

Practice - Differential Privacy (DP)

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does Differential Privacy aim to protect?

💡 Hint: Think about what happens when someone’s data is added or removed.

Question 2 Easy

Name one mechanism of Differential Privacy.

💡 Hint: It adds noise to what's being computed.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does Differential Privacy ensure regarding individual data points?

They can significantly influence the model output.
They do not influence model output significantly.
They are exposed in training data.

💡 Hint: Remember how data contributes to model predictions.

Question 2

True or False: The Laplace Mechanism adds Gaussian noise to numerical queries.

True
False

💡 Hint: Recall the specific noises associated with different mechanisms.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

If a company decides to implement Differential Privacy on their data, but they set ε too low, what potential issues could arise?

💡 Hint: Think about how strict privacy requirements interact with accuracy.

Challenge 2 Hard

How would you explain to a non-technical person how Differential Privacy works using the analogy of a party?

💡 Hint: Consider what distractions would prevent identifying specifics.

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Reference links

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