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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the primary goal of differential privacy?
π‘ Hint: Think about how the inclusion of a data point would affect the outcome.
Question 2
Easy
Define robustness in the context of machine learning.
π‘ Hint: Consider how models react to unexpected changes.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the main purpose of differential privacy?
π‘ Hint: Consider what privacy guarantees it provides.
Question 2
True or False: Adversarial training can reduce a model's performance on clean data.
π‘ Hint: Think about the implications of training on different data.
Solve 2 more questions and get performance evaluation
Push your limits with challenges.
Question 1
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.
π‘ Hint: Consider use-cases where sensitive data must remain confidential.
Question 2
Critique a current ML model using federated learning regarding its privacy implications. Identify strengths and weaknesses.
π‘ Hint: Focus on how data is managed between clients and servers.
Challenge and get performance evaluation