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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is bias in machine learning?
💡 Hint: Think about what assumptions the model makes.
Question 2
Easy
Give an example of a high bias model.
💡 Hint: Consider relationships that aren't straight.
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 high bias in a model typically lead to?
- Overfitting
- Underfitting
- Perfect fit
💡 Hint: Think about the relationship between complexity and accuracy.
Question 2
True or False: A high bias model can still perform well on training datasets.
- True
- False
💡 Hint: Reflect on whether simplicity aids or hinders performance.
Solve and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design an experiment to test the effect of bias on machine learning models using both high bias and low bias settings. Provide a detailed plan on how you would analyze the results.
💡 Hint: Consider using polynomial regression for flexible modeling.
Question 2
Critique a biased model and propose adjustments to reduce bias without significantly increasing variance. Provide examples.
💡 Hint: Think about model flexibility carefully!
Challenge and get performance evaluation