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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is overfitting?
💡 Hint: Think about how well it performs on unseen data.
Question 2
Easy
List one cause of underfitting.
💡 Hint: Consider how complex the data is.
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 purpose of L1 regularization?
- To minimize the absolute values of coefficients
- To minimize the squared values of coefficients
- To remove irrelevant features
💡 Hint: Consider what happens to features with small importance.
Question 2
True or False: L2 regularization is also known as Ridge regression.
- True
- False
💡 Hint: Think about the naming of regression techniques.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with multicollinearity, discuss how you would decide between Lasso and Ridge regression, and justify your answer.
💡 Hint: Think about the nature of your features and their relationships.
Question 2
You have a dataset that is both large and complex. Explain your choice of regularization method and validation technique.
💡 Hint: Consider the model's flexibility and evaluation accuracy.
Challenge and get performance evaluation