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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 how data might reflect past inequalities.
Question 2
Easy
Define re-sampling in one sentence.
💡 Hint: How do we balance contributions from different groups?
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 does re-sampling aim to achieve in machine learning?
- To enhance data quality.
- To balance demographic representation.
- To increase model complexity.
💡 Hint: Consider how unbalanced data affects model predictions.
Question 2
True or False: Re-weighing assigns equal importance to all samples in a dataset.
- True
- False
💡 Hint: What does it mean to prioritize certain samples?
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Create a questionnaire to assess bias in a dataset used for hiring. What aspects will you analyze?
💡 Hint: Think about what categories of bias could impact hiring.
Question 2
Design a scenario where re-sampling could fail and lead to worse outcomes. Describe how to avoid this in practice.
💡 Hint: Consider negative outcomes from one-sided approaches.
Challenge and get performance evaluation