#6: Scikit-learn 4: Preprocessing 4: Scaling data with outliers using RobustScaler

The video discusses how to and how not-to scale data with outliers and use of RobustScaler in Scikit-learn in Python. Timeline (Python 3.8) 00:00 - Welcome 00:17 - Outline of video 00:42 - Suggested steps in scaling 01:10 - Why use .RobustScaler() with outliers? 03:48 - Open Jupyter notebook 04:18 - Create data with outliers 04:18 - -------- CORRECTION ------- "I meant to say 'rows' while creating the array" (and not 'columns') 04:57 - Outlier data: RobustScaler: .fit() and .transform() 06:22 - Outlier data: StandardScaler: .fit() and .transform() 07:00 - Outlier data: MaxAbsScaler: .fit() and .transform() 07:14 - Outlier data: MinMaxScaler: .fit() and .transform() 07:32 - Create data with outliers 09:00 - Outlier data: MinMaxScaler: .fit_transform() 09:53 - Outlier data: RobustScaler: .fit_transform() 10:48 - Ending notes