Practice - Outputs and Interpretation
Practice Questions
Test your understanding with targeted questions
Define bias in machine learning.
💡 Hint: Think about how models learn from historical data.
What does XAI stand for?
💡 Hint: Focus on interpretability.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What term refers to systematic prejudice in AI predictions?
💡 Hint: Think about discrimination in algorithms.
True or False: LIME is used for global explanations.
💡 Hint: Consider which predictions LIME focuses on.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
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.
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.
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Reference links
Supplementary resources to enhance your learning experience.
- What Is Bias in Machine Learning?
- Understanding Explainable AI (XAI)
- The Importance of Accountability in AI Systems
- LIME: Local Interpretable Model-agnostic Explanations
- SHAP (SHapley Additive exPlanations)
- The Ethics of Artificial Intelligence and Robotics
- Introduction to the Fairness and Transparency in Artificial Intelligence
- Understanding Machine Learning Fairness