Practice Step 2: Data Preprocessing - 9.3 | Chapter 9: End-to-End Machine Learning Project – Predicting Student Exam Performance | Machine Learning Basics
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9.3 - Step 2: Data Preprocessing

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the purpose of mapping categorical variables?

💡 Hint: Think of why numbers are easier for algorithms than words.

Question 2

Easy

Name the pandas function used for mapping.

💡 Hint: What do you use in Python to transform data?

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 is the mapping for 'no' in the context of 'preparation_course'?

  • 1
  • 0
  • 2

💡 Hint: Remember the mapping assigned in the data preprocessing step.

Question 2

Is it true that without preprocessing, machine learning models cannot process categorical data?

  • True
  • False

💡 Hint: Think about what type of data is required for algorithms to work.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Given a dataset with multiple categorical features, design a mapping strategy that efficiently converts these into numerics. Consider how you would handle unseen categories when applying your mapping.

💡 Hint: Think about how categories can change over time and how you will maintain integrity in your model.

Question 2

Reflect on a dataset you encountered. Identify a categorical feature and explain how you would map it. Discuss the implications of not mapping it correctly.

💡 Hint: Consider the impact of each category on your data analysis.

Challenge and get performance evaluation