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Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define overfitting in your own words.
π‘ Hint: Think about how models memorize the training set instead of learning patterns.
Question 2
Easy
What is K-Fold cross-validation?
π‘ Hint: Consider the mechanism of creating multiple training and validation sets.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the main purpose of regularization?
π‘ Hint: Consider what affects a model's ability to generalize.
Question 2
True or False: Lasso regression can reduce some coefficients to zero.
π‘ Hint: Think about how each regularization technique works.
Solve and get performance evaluation
Push your limits with challenges.
Question 1
You find that a model with Lasso regression has a high training error but performs well on the test set. Why might this happen?
π‘ Hint: Consider how feature selection impacts the training phase.
Question 2
If you applied both L1 and L2 regularization to the same model, what would the expected outcome be?
π‘ Hint: Think about what combining penalties would achieve.
Challenge and get performance evaluation