5.1 - What is Data Preprocessing?
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Practice Questions
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What is data preprocessing?
💡 Hint: Think about the steps needed before analyzing data.
Why is handling missing data important?
💡 Hint: Recall the effect of missing information on predictions.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does data preprocessing involve?
💡 Hint: Focus on the faults related to data.
True or False: All machine learning algorithms can handle missing values without preprocessing.
💡 Hint: Reflect on processing methods needed.
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Challenge Problems
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Suppose you have a dataset with over 25% missing values in a crucial feature. How would you address this before modeling?
💡 Hint: Analyze the impact of missing data percentages.
If a feature comprises numbers in differing ranges (e.g., 1-10 and 1000-10000), how would you prepare this data for a machine learning model?
💡 Hint: Reflect on why feature dominance can alter predictions.
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