Practice - Privacy-Aware and Robust Machine Learning
Practice Questions
Test your understanding with targeted questions
What is the primary goal of differential privacy?
💡 Hint: Think about how the inclusion of a data point would affect the outcome.
Define robustness in the context of machine learning.
💡 Hint: Consider how models react to unexpected changes.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is the main purpose of differential privacy?
💡 Hint: Consider what privacy guarantees it provides.
True or False: Adversarial training can reduce a model's performance on clean data.
💡 Hint: Think about the implications of training on different data.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
Design a machine learning model for a medical application that needs differential privacy. Discuss implications of using different privacy techniques and their effects on the model's performance.
💡 Hint: Consider use-cases where sensitive data must remain confidential.
Critique a current ML model using federated learning regarding its privacy implications. Identify strengths and weaknesses.
💡 Hint: Focus on how data is managed between clients and servers.
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Reference links
Supplementary resources to enhance your learning experience.