Practice What is Feature Engineering? - 2.4.1 | 2. Data Wrangling and Feature Engineering | Data Science Advance
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What is Feature Engineering?

2.4.1 - What is Feature Engineering?

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is feature engineering?

💡 Hint: Think about how transforming data could impact model predictions.

Question 2 Easy

Name one technique used in feature extraction.

💡 Hint: Consider how we turn text into numbers.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does feature engineering primarily focus on?

Cleaning data
Creating and modifying features
Visualizing data

💡 Hint: Consider the aspect of data handling that enhances model insights.

Question 2

True or False: Feature selection is unimportant because all the features in a dataset should be used in a model.

True
False

💡 Hint: Reflect on why simplifying a model can lead to better performance.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You're tasked with improving the accuracy of a model predicting house prices. Your dataset includes features such as square footage, number of bedrooms, and location. What new feature could you construct, and why would it benefit the model?

💡 Hint: Think about ratios that might offer better insights.

Challenge 2 Hard

Analyze a dataset containing customer transactions and brainstorm three new features that could be valuable for predicting customer lifetime value.

💡 Hint: What metrics can give insight into long-term customer relationships?

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