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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is data cleaning?
💡 Hint: Think about what happens when data is inaccurate.
Question 2
Easy
What is feature engineering?
💡 Hint: Consider how we improve data for models.
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 goal of data preprocessing?
- To make data visually appealing
- To prepare data for analysis
- To secure data
💡 Hint: Remember, it's about ensuring the data is usable.
Question 2
True or False: Outlier treatment has no impact on the quality of data analysis.
- True
- False
💡 Hint: How does ignoring outliers affect results?
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are given a dataset with many missing values and some extreme outliers. Outline your approach to clean and prepare the data for analysis.
💡 Hint: Consider both statistical techniques and business context when dealing with anomalies.
Question 2
Describe a scenario where feature engineering significantly improved a model's performance. What features would you create and why?
💡 Hint: Think about relationships between existing variables.
Challenge and get performance evaluation