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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is a black box model?
💡 Hint: Think about how transparent a model's decisions are.
Question 2
Easy
What does XAI stand for?
💡 Hint: What do we call AI methods that clarify how decisions are made?
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 primary focus of LIME?
- Global explanation of model predictions
- Local interpretation of individual predictions
- Enhancing model accuracy
💡 Hint: Think about whether LIME is for one prediction or many.
Question 2
True or False: SHAP is solely focused on local explanations.
- True
- False
💡 Hint: Consider the breadth of SHAP's capabilities.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Consider a healthcare AI system that predicts heart disease risk but does not reveal how it reaches its conclusions. Apply the concepts of LIME and SHAP to propose how you would communicate the model's predictions to patients.
💡 Hint: Think about the needs of patients for understanding their health conditions.
Question 2
Imagine you are a data scientist responsible for an AI model used in hiring. The management demands no bias in decisions, yet the model is a black box. How might you employ SHAP to tackle these concerns?
💡 Hint: Consider how transparency could influence hiring outcomes.
Challenge and get performance evaluation