Practice - DP in ML Training
Practice Questions
Test your understanding with targeted questions
What does DP-SGD stand for?
💡 Hint: Think about privacy in the context of gradient descent.
What is the purpose of adding noise to gradients?
💡 Hint: Consider why we want to obscure specific contributions.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does DP-SGD do during the model training process?
💡 Hint: Focus on the process of how gradients are updated.
True or False: Gradient clipping has no impact on privacy.
💡 Hint: Think about how influence of samples is managed.
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Challenge Problems
Push your limits with advanced challenges
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.
Propose a novel approach to improve privacy efficiency in DP-SGD while maintaining model performance.
💡 Hint: Think about how to dynamically manage privacy levels.
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Reference links
Supplementary resources to enhance your learning experience.