Practice Outputs and Interpretation - 3.3.2.1.4 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 14) | Machine Learning
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3.3.2.1.4 - Outputs and Interpretation

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

Define bias in machine learning.

💡 Hint: Think about how models learn from historical data.

Question 2

Easy

What does XAI stand for?

💡 Hint: Focus on interpretability.

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 term refers to systematic prejudice in AI predictions?

  • Fairness
  • Bias
  • Transparency

💡 Hint: Think about discrimination in algorithms.

Question 2

True or False: LIME is used for global explanations.

  • True
  • False

💡 Hint: Consider which predictions LIME focuses on.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Analyze a proposed AI hiring model that only selects candidates from specific universities. Discuss potential biases and suggest remodeling strategies.

💡 Hint: Consider the implications of filtering candidates based on educational background.

Question 2

Propose a method to ensure that a machine learning algorithm predicting healthcare outcomes complies with privacy regulations.

💡 Hint: Think about how to balance data utility with personal rights.

Challenge and get performance evaluation