Practice Introduction to Explainable AI (XAI): Illuminating the Black Box - 3 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 14) | Machine Learning
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3 - Introduction to Explainable AI (XAI): Illuminating the Black Box

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does XAI stand for?

πŸ’‘ Hint: Think about what making AI decisions understandable means.

Question 2

Easy

Describe how LIME generates explanations for a specific prediction.

πŸ’‘ Hint: Consider what happens when you change the inputs slightly.

Practice 1 more question 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 primary aim of Explainable AI?

  • To improve model accuracy
  • To make AI decisions transparent
  • To reduce computing power

πŸ’‘ Hint: Remember the importance of trust in AI.

Question 2

True or False: SHAP only provides local explanations.

  • True
  • False

πŸ’‘ Hint: Think about how many types of explanations SHAP offers.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design an AI system for financial advice. Explain how you would ensure it is explainable for various users, including regulatory oversight.

πŸ’‘ Hint: Think about the types of users and their understanding needs.

Challenge and get performance evaluation