Practice Understanding Robustness - 13.4.1 | 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 robustness in machine learning?

πŸ’‘ Hint: Consider what it means to be strong or resilient.

Question 2

Easy

Name one type of attack that threatens model robustness.

πŸ’‘ Hint: Think about inputs that are misleading.

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 does robustness in ML refer to?

  • Maintaining accuracy despite attacks
  • Speed of model training
  • Size of the model

πŸ’‘ Hint: Think about survival under pressure.

Question 2

True or False: Adversarial examples can appear normal to a human observer.

  • True
  • False

πŸ’‘ Hint: Consider how our eyes might be tricked.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a hypothetical machine learning model that can withstand an adversarial attack. Discuss the key features that would enhance its robustness.

πŸ’‘ Hint: Think about how to strengthen the model's defenses.

Question 2

Analyze the impact of model extraction on intellectual property. How could such attacks be mitigated in practice?

πŸ’‘ Hint: Consider strategies to protect sensitive information.

Challenge and get performance evaluation