Practice Black Box Prediction (3.3.1.1.2) - Advanced ML Topics & Ethical Considerations (Weeks 14)
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Black Box Prediction

Practice - Black Box Prediction

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Practice Questions

Test your understanding with targeted questions

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?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

Challenge 2 Hard

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.

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