What are some effective data preprocessing techniques in Python?
Some effective techniques include handling missing values, normalization, encoding categorical variables, and feature scaling.
Can you explain how to handle missing values?
You can handle missing values by removing them, filling them with mean/median/mode, or using interpolation.
What is normalization and why is it important?
Normalization scales the data to a specific range, usually [0, 1], which helps improve the performance of machine learning algorithms.
How do I encode categorical variables in Python?
You can use techniques like one-hot encoding or label encoding, which can be implemented using libraries like pandas.
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