Practice Data Preparation And Initial Review (4.2.1) - Supervised Learning - Regression & Regularization (Weeks 4)
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Data Preparation and Initial Review

Practice - Data Preparation and Initial Review

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the purpose of data preprocessing?

💡 Hint: Think about how data is prepared for machine learning models.

Question 2 Easy

Define the test set in a machine learning context.

💡 Hint: Remember, it should not be used during training!

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is one purpose of data preprocessing?

To reduce dataset size
To prepare data for analysis
To create new features

💡 Hint: Why do we clean and adjust the data before analysis?

Question 2

True or False: The test set should be used during model training.

True
False

💡 Hint: Consider which data should guide the model's learning process.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You have access to a dataset containing housing prices but find that several features contain missing values. Describe the steps you would take to prep this data for modeling, addressing missing values and potential outliers.

💡 Hint: Consider the importance of each step and why it matters.

Challenge 2 Hard

Reflect on a scenario where your linear regression model shows high performance on training data but poor performance on test data. What steps would you consider to address this issue?

💡 Hint: Think about potential causes and solutions systematically.

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Reference links

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