Practice Robustness in Machine Learning - 13.4 | 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: Think about a model's performance under stress.

Question 2

Easy

Name one type of attack on machine learning models.

πŸ’‘ Hint: Consider attacks that can confuse the model.

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 goal of robustness in machine learning?

  • To enhance accuracy in all scenarios
  • To ensure performance under duress
  • To make models simpler

πŸ’‘ Hint: Think about models challenged by adversarial changes.

Question 2

True or false: Data poisoning can permanently damage a model's training.

  • True
  • False

πŸ’‘ Hint: Consider the impact on training data.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Develop a detailed defense strategy against a hypothetical scenario of model extraction in a cloud-based ML system.

πŸ’‘ Hint: How can limiting access help secure the model?

Question 2

Create a short narrative explaining how data poisoning could impact a healthcare application using ML.

πŸ’‘ Hint: What happens if vital patient data is altered?

Challenge and get performance evaluation