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Learn imputation, variable encoding, discretization, feature extraction, how to work with datetime, outliers, and more.
Create lag, window and seasonal features, perform imputation and encoding, extract datetime variables, remove outliers, and more.
Learn filter, wrapper, and embedded methods, recursive feature elimination, exhaustive search, feature shuffling & more.
Learn to over-sample and under-sample your data, apply SMOTE, ensemble methods, and cost-sensitive learning.