Practice Motivation and Importance - 13.1.1 | 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 is data leakage?

πŸ’‘ Hint: Think about what could happen if sensitive data were exposed.

Question 2

Easy

Name one attack that can compromise model privacy.

πŸ’‘ Hint: Consider attacks that aim to infer original data.

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 data leakage?

  • A method of improving model accuracy
  • The exposure of sensitive data
  • A privacy protection technique

πŸ’‘ Hint: Consider the risks involved when sensitive information is not protected.

Question 2

True or False: Membership inference attacks aim to determine whether a data point was used in training.

  • True
  • False

πŸ’‘ Hint: Remember the intent behind these types of attacks.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Analyze a recent data breach incident. Discuss the privacy implications and how the breach could have been prevented.

πŸ’‘ Hint: Look for actual cases and consider both technical and ethical perspectives.

Question 2

Consider a machine learning application handling sensitive user data. Develop a set of ethical guidelines that must be adhered to for preserving data privacy.

πŸ’‘ Hint: Think about how you would ensure respect for individuals’ privacy.

Challenge and get performance evaluation