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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does DP-SGD stand for?
💡 Hint: Think about privacy in the context of gradient descent.
Question 2
Easy
What is the purpose of adding noise to gradients?
💡 Hint: Consider why we want to obscure specific contributions.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does DP-SGD do during the model training process?
- Adds noise to data
- Adds noise to gradients
- Removes data points
💡 Hint: Focus on the process of how gradients are updated.
Question 2
True or False: Gradient clipping has no impact on privacy.
- True
- False
💡 Hint: Think about how influence of samples is managed.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
What is the consequence of applying too much noise in DP-SGD, and how can you assess if noise levels are appropriate?
💡 Hint: Consider the balance between privacy and visibility.
Question 2
Propose a novel approach to improve privacy efficiency in DP-SGD while maintaining model performance.
💡 Hint: Think about how to dynamically manage privacy levels.
Challenge and get performance evaluation