Practice Feature Engineering Principles (1.4.6) - ML Fundamentals & Data Preparation
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Feature Engineering Principles

Practice - Feature Engineering Principles

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is feature engineering?

💡 Hint: Think about how you can improve data for better predictions.

Question 2 Easy

Give an example of creating a new feature from existing data.

💡 Hint: Consider other physical characteristics.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main goal of feature engineering?

To create more data points.
To improve machine learning model performance.
To reduce computation time.

💡 Hint: Think about what features provide the most value to a model.

Question 2

True or False: Polynomial features can help capture non-linear relationships.

True
False

💡 Hint: Remember how curves differ from straight lines.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You have a dataset with customer reviews, numerical ratings, and timestamps. How would you engineer features to predict future purchase behavior?

💡 Hint: Think about customer engagement metrics.

Challenge 2 Hard

Imagine your model is overfitting due to engineered features. What steps would you take to mitigate this?

💡 Hint: Think about how to balance complexity with performance.

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Reference links

Supplementary resources to enhance your learning experience.