Practice - Prepare Data for Clustering with Precision
Practice Questions
Test your understanding with targeted questions
What is EDA and why is it important?
💡 Hint: Think about the first steps in data analysis.
Name one method to handle missing data.
💡 Hint: Consider filling in the blanks in a dataset.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does EDA stand for?
💡 Hint: Think about analyzing data structures.
True or False: One-Hot Encoding increases the dimensions of the dataset.
💡 Hint: Consider how many features a categorical variable turns into.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
Imagine you have customer data for an online retailer with multiple missing fields. Discuss how you would handle these missing values before clustering and why your chosen strategy could lead to better results.
💡 Hint: Consider how the volume of missing data affects your decision.
You are given a dataset where one feature ranges from 0 to 1 and another from 0 to 1000. Explain how this difference in range could affect your clustering results and outline how you would address it.
💡 Hint: Consider the implications on distance metrics.
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Reference links
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