Practice Advanced ML Topics & Ethical Considerations - 7 | Module 7: Advanced ML Topics & Ethical Considerations (Weeks 14) | Machine Learning
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7 - Advanced ML Topics & Ethical Considerations

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is bias in the context of machine learning?

πŸ’‘ Hint: Think about how data reflects societal stereotypes.

Question 2

Easy

Name one method used to ensure fairness in ML models.

πŸ’‘ Hint: Consider how different demographic groups are treated by AI.

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 purpose of Explainable AI?

  • To increase model accuracy
  • To make AI transparent
  • To improve data collection

πŸ’‘ Hint: Think about how users benefit from understanding AI decisions.

Question 2

True or False: Bias is always intentional in machine learning.

  • True
  • False

πŸ’‘ Hint: Consider how societal biases can surface in technology.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a machine learning approach to address bias in credit scoring models. Describe interventions across each stage of the machine learning lifecycle.

πŸ’‘ Hint: Think about the sources of bias at different stages of the ML process.

Question 2

Evaluate the ethical implications of using AI in healthcare diagnostics where bias might affect treatment recommendations. Propose a framework for addressing these biases.

πŸ’‘ Hint: Focus on equitable access to healthcare as a primary concern.

Challenge and get performance evaluation