01What is 'Data Imputation'?
02Why is 'Feature Scaling' (like Standardization) essential for many AI models?
03What is 'One-Hot Encoding' used for?
04What is 'Data Leakage'?
05How does Pydantic differ from pandas in a production AI pipeline?
06What is the difference between `StandardScaler` and `MinMaxScaler`?
07When should you perform 'Label Encoding' instead of 'One-Hot Encoding'?
08What is the purpose of a 'Validation Set'?
09What is 'Outlier Detection'?
10In pandas, what does `df.dropna()` do?