Practice - Propose Concrete Mitigation Strategies
Practice Questions
Test your understanding with targeted questions
What is historical bias?
💡 Hint: Think about societal influences on data.
Explain what representation bias means.
💡 Hint: Consider diversity in the training data.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is the main focus of bias mitigation strategies in machine learning?
💡 Hint: Think about the implications of bias.
True or False: Algorithmic bias cannot occur if the dataset is balanced.
💡 Hint: Reflect on algorithm design principles.
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Challenge Problems
Push your limits with advanced challenges
Propose a specific use case where you would apply a holistic bias mitigation strategy, detailing what strategies you would employ and why.
💡 Hint: Think about all stages of the model lifecycle.
You have a model that shows great accuracy but significantly higher false positive rates for minority groups. Discuss how you would approach mitigating these discriminatory outcomes.
💡 Hint: Consider the implications of the model’s design.
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Reference links
Supplementary resources to enhance your learning experience.