Practice Train And Predict (4.1.5) - Supervised Learning - Regression & Regularization (Weeks 3)
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Train and Predict

Practice - Train and Predict

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the purpose of linear regression?

💡 Hint: Think about predictions based on relationships.

Question 2 Easy

Define MSE in the context of regression.

💡 Hint: Remember it deals with squared differences.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does the acronym MSE stand for?

Mean Squared Error
Mean Standard Error
Mode Squared Error

💡 Hint: It relates to the squares of the prediction errors.

Question 2

True or False: A model with high bias performs well on training data.

True
False

💡 Hint: Think about how model simplicity affects prediction.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design an experiment to compare the effectiveness of linear regression vs polynomial regression on a dataset with a known non-linear relationship.

💡 Hint: Consider how each model captures the true relationship.

Challenge 2 Hard

How would you modify a model showing high variance? Provide detailed steps.

💡 Hint: What approaches can control overfitting?

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Reference links

Supplementary resources to enhance your learning experience.