01. Module Overview
02. Converting Continuous Data to Categorical
03. Demo- Convert Numeric Data to Binary Categories Using a Binarizer
04. Demo- Using the KBinsDiscretizer to Categorize Numeric Values
05. Demo- Using Bin Values to Flag Outliers
06. Scaling Data
07. Demo- Scaling with the MaxAbsScaler
08. Demo- Scaling with the MinMaxScaler
09. Custom Transformations
10. Demo- Performing Custom Transforms Using the FunctionTransformer
11. Generating Polynomial Features
12. Demo- Using Polynomial Features to Transform Data
13. Transforming Features to Gaussian-like Distributions Using Power Transformers
14. Demo- Working with Chi Squared Distributed Input Features
15. Demo- Applying Power Transformers to Get Normal Distributions
16. Transforming Data to Normal or Uniform Distributions Using Quantile Transformers
17. Demo- Tranforming to a Normal Distribution Using the QuantileTransformer
18. Summary and Further Study