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

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

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.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

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.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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.

Question 2

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?

Challenge and get performance evaluation