Practice Advantages for Privacy - 13.3.2 | 13. Privacy-Aware and Robust Machine Learning | Advance Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does Federated Learning primarily aim to protect?

πŸ’‘ Hint: Think about where the data is stored during training.

Question 2

Easy

Name one method that can be combined with Federated Learning to enhance privacy.

πŸ’‘ Hint: What technique adds noise to data outputs?

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 is the main benefit of Federated Learning?

  • A. Increases data exposure
  • B. Keeps data on user devices
  • C. Requires all data on the server

πŸ’‘ Hint: Think about the meaning of federated in this context.

Question 2

True or False: Differential Privacy can be applied independently of Federated Learning.

  • True
  • False

πŸ’‘ Hint: Consider the scenarios where both concepts work together.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a privacy-preserving application leveraging Federated Learning and Differential Privacy. Discuss potential user benefits and challenges.

πŸ’‘ Hint: Consider how you would approach privacy in health data management.

Question 2

Identify and evaluate the risks of data breaches that still apply even with Federated Learning and suggest mitigations.

πŸ’‘ Hint: Think about how real-world applications manage attacks on their systems.

Challenge and get performance evaluation