Practice Types of Feature Engineering Techniques - 2.5 | 2. Data Wrangling and Feature Engineering | Data Science Advance
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Types of Feature Engineering Techniques

2.5 - Types of Feature Engineering Techniques

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does feature extraction involve?

💡 Hint: Think about how we create new information from existing data.

Question 2 Easy

Name one method of feature transformation.

💡 Hint: Consider how we might adjust the distribution of our data.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the main purpose of feature extraction?

To normalize data
To derive new features from data
To remove irrelevant features

💡 Hint: Think about how we create more information from what we have.

Question 2

True or False: Feature transformation always improves model performance.

True
False

💡 Hint: Consider your understanding of feature distribution.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a feature extraction process for a dataset containing customer reviews to identify sentiment features.

💡 Hint: Focus on how to convert reviews into structured data.

Challenge 2 Hard

You have a dataset that includes date-time features. How would you extract useful components to enhance modeling?

💡 Hint: Think about how different times of the day might affect customer behaviors.

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