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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is normalization in the context of machine learning?
💡 Hint: Think about why having different scales in features could be problematic.
Question 2
Easy
Name one method of normalization.
💡 Hint: Remember 'Min-Max' scales data between 0 and 1.
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 primary purpose of normalization in machine learning?
- To remove data
- To adjust scales of features
- To enhance data quality
💡 Hint: Think about how different scales can affect model behavior.
Question 2
True or False: Normalization helps models to process data consistently regardless of original value ranges.
- True
- False
💡 Hint: Reflect on the impact of varying scales.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Propose a comprehensive workflow for normalizing a dataset with multiple features, including outliers. Describe each step clearly.
💡 Hint: Think sequentially about how to process with outliers included.
Question 2
Given a hypothetical scenario with fluctuating readings from IoT sensors due to environmental changes, how would you adapt your normalization methods over time?
💡 Hint: Consider what practices could maintain accuracy over time.
Challenge and get performance evaluation