Practice Core Concepts (3.1) - Supervised Learning - Regression & Regularization (Weeks 4)
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Core Concepts

Practice - Core Concepts

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is underfitting?

💡 Hint: Think about how well the model fits the training data.

Question 2 Easy

What is overfitting?

💡 Hint: Consider how a student remembers answers without understanding.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary goal of regularization?

To increase model complexity
To reduce overfitting
To decrease training time

💡 Hint: Focus on why we add penalties to models.

Question 2

True or False: L1 regularization can lead to some coefficients being exactly zero.

True
False

💡 Hint: Think about what each type of regularization does.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a dataset with numerous features, how would you decide on the ideal regularization technique? Explain your reasoning thoroughly.

💡 Hint: Think about the data structure and your modeling goal.

Challenge 2 Hard

You have implemented K-Fold Cross-Validation but find that some folds contain very few samples of a minority class. What steps can you take to address this issue?

💡 Hint: Consider how class distribution affects performance metrics.

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