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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is bias in the context of machine learning?
💡 Hint: Think about outcomes that are influenced by the training data.
Question 2
Easy
Define fairness in AI systems.
💡 Hint: Consider how different demographics are impacted by AI decisions.
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 definition of bias in machine learning?
- Fair treatment across demographics
- Systematic prejudice in outcomes
- Weights assigned to data
💡 Hint: Think about how certain groups might be systematically affected.
Question 2
True or False: Transparency in AI only matters for technical users.
- True
- False
💡 Hint: Consider the importance of trust in technology.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a machine learning project aimed at AI hiring. Identify potential bias points from data collection to model deployment and propose strategies for mitigation.
💡 Hint: Think about the entire lifecycle of the data and the model.
Question 2
Evaluate an AI's fairness in predicting loan approvals. Determine if there’s evidence of disparate impact and suggest improvements.
💡 Hint: Check if the model performs consistently across different demographic groups.
Challenge and get performance evaluation