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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is EDA and why is it important?
💡 Hint: Think about the first steps in data analysis.
Question 2
Easy
Name one method to handle missing data.
💡 Hint: Consider filling in the blanks in a dataset.
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 does EDA stand for?
- Exploratory Data Analysis
- Enhanced Data Analysis
- Elemental Data Assessment
💡 Hint: Think about analyzing data structures.
Question 2
True or False: One-Hot Encoding increases the dimensions of the dataset.
- True
- False
💡 Hint: Consider how many features a categorical variable turns into.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
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.
Question 2
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.
Challenge and get performance evaluation