Practice Feature Scaling - 5.8 | Data Cleaning and Preprocessing | Data Science Basic
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Feature Scaling

5.8 - Feature Scaling

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is normalization?

💡 Hint: Think of how values are limited to a specific range.

Question 2 Easy

What is the primary goal of standardization?

💡 Hint: Consider the shape of a normal distribution.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the purpose of normalization in feature scaling?

To reduce variance
To bring all features to a common scale
To eliminate missing values

💡 Hint: Think about how different features are represented numerically.

Question 2

True or False: Standardization rescales data based on the maximum feature value.

True
False

💡 Hint: Remember how data is centered in statistical terms.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You have a dataset with 'Height in cm' and 'Weight in kg'. How would you decide whether to normalize or standardize this data before using it in a machine learning model?

💡 Hint: Consider ranges and distributions of the features.

Challenge 2 Hard

Create a small dataset containing two features: Age and Salary. Demonstrate how to apply both normalization and standardization using code, explaining your steps.

💡 Hint: Ensure to use respective scaling libraries.

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