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This repository is totally focused on Feature Engineering Concepts in detail, I hope you'll find it helpful.

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zuhaib1214/Feature-Engineering

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Column Transformer And Pipielining
Column Transformer And Pipielining
 
 
EDA
EDA
 
 
Encoding Categorical Data(Ordinal Encoding Label Encoding One Hot Encoding)
Encoding Categorical Data(Ordinal Encoding Label Encoding One Hot Encoding)
 
 
Encoding Numerical Data(Binarizatin Discritization
Encoding Numerical Data(Binarizatin Discritization
 
 
Feature Construction and Splitting
Feature Construction and Splitting
 
 
Handling Missing Data (IMputation Techniques and CCA)
Handling Missing Data (IMputation Techniques and CCA)
 
 
Outlier Detection and removal(Z-score Percentile and winsorization
Outlier Detection and removal(Z-score Percentile and winsorization
 
 
Pandas and numpy
Pandas and numpy
 
 
Principal Component Analysis
Principal Component Analysis
 
 
Scalling NUmerical Data(Standardization Normalization Function Transformer Power Transformer)
Scalling NUmerical Data(Standardization Normalization Function Transformer Power Transformer)
 
 
Understanding your data(csv and json files)
Understanding your data(csv and json files)
 
 
handling dates and mixed information data
handling dates and mixed information data
 
 
LICENSE
LICENSE
 
 
README.md
README.md
 
 

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Feature-Engineering

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This repository is totally focused on Feature Engineering Concepts in detail, I hope you'll find it helpful.

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standardization feature-engineering principal-component-analysis binarization z-score normalisation onehot-encoding simpleimputer ordinal-encoding labelencoder knn-imputer winsorization iterative-imputer percentile-method discritisation mean-median-imputation frequent-value-imputation

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