9.3 - Step 2: Data Preprocessing
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Practice Questions
Test your understanding with targeted questions
What is the purpose of mapping categorical variables?
💡 Hint: Think of why numbers are easier for algorithms than words.
Name the pandas function used for mapping.
💡 Hint: What do you use in Python to transform data?
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the mapping for 'no' in the context of 'preparation_course'?
💡 Hint: Remember the mapping assigned in the data preprocessing step.
Is it true that without preprocessing, machine learning models cannot process categorical data?
💡 Hint: Think about what type of data is required for algorithms to work.
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Challenge Problems
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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.
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.
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