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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 why we need accurate data for analysis.
Question 2
Easy
Why is normalization needed?
💡 Hint: Consider how different units can affect calculations.
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 cleaning?
- To analyze the data
- To correct inaccuracies
- To add new data
💡 Hint: Remember the importance of accurate data for reliable analysis.
Question 2
True or False: Normalization is unnecessary if all data is already on a similar scale.
- True
- False
💡 Hint: Think about data representation in machine learning models.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Given a dataset with missing values, describe two different methods you could use to address the issue, including the potential consequences of each approach.
💡 Hint: Think about the trade-offs between data integrity and accuracy in predictions.
Question 2
Imagine you have collected sensor data with significant outliers due to equipment malfunction. How would you identify and handle these outliers in your preprocessing steps?
💡 Hint: Consider how outliers can skew the results in statistical analyses.
Challenge and get performance evaluation