Skip to content

jainharsh644/Tutorial-Feature-Engineering-in-ML

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
Churn_Modelling.csv
Churn_Modelling.csv
 
 
FE - CROSS VALIDATION (Part 16).ipynb
FE - CROSS VALIDATION (Part 16).ipynb
 
 
FE - Categorical Missing Values Imputation (Part 6).ipynb
FE - Categorical Missing Values Imputation (Part 6).ipynb
 
 
FE - Feature Selection Techniques (Part 13).ipynb
FE - Feature Selection Techniques (Part 13).ipynb
 
 
FE - Feature Selection Techniques (Part 14).ipynb
FE - Feature Selection Techniques (Part 14).ipynb
 
 
FE - HANDLING OUTLIERS (Part 15).ipynb
FE - HANDLING OUTLIERS (Part 15).ipynb
 
 
FE - Handle Categorical Features (Part 7).ipynb
FE - Handle Categorical Features (Part 7).ipynb
 
 
FE - Handle Categorical Features (Part 8).ipynb
FE - Handle Categorical Features (Part 8).ipynb
 
 
FE - Handle Categorical Features (Part 9).ipynb
FE - Handle Categorical Features (Part 9).ipynb
 
 
FE - Missing Values Imputation (Part 1).ipynb
FE - Missing Values Imputation (Part 1).ipynb
 
 
FE - Missing Values Imputation (Part 2).ipynb
FE - Missing Values Imputation (Part 2).ipynb
 
 
FE - Missing Values Imputation (Part 3).ipynb
FE - Missing Values Imputation (Part 3).ipynb
 
 
FE - Missing Values Imputation (Part 4).ipynb
FE - Missing Values Imputation (Part 4).ipynb
 
 
FE - Missing Values Imputation (Part 5).ipynb
FE - Missing Values Imputation (Part 5).ipynb
 
 
FE - Transformation Techniques (Part 10).ipynb
FE - Transformation Techniques (Part 10).ipynb
 
 
FE - Transformation Techniques (Part 11).ipynb
FE - Transformation Techniques (Part 11).ipynb
 
 
FE - Transformation Techniques (Part 12).ipynb
FE - Transformation Techniques (Part 12).ipynb
 
 
IMBALANCED DATA - ALL TECHNIQUES.ipynb
IMBALANCED DATA - ALL TECHNIQUES.ipynb
 
 
README.md
README.md
 
 
mercedes.csv
mercedes.csv
 
 
santander_train.csv
santander_train.csv
 
 
titanic train.csv
titanic train.csv
 
 

Repository files navigation

Feature Engineering Techniques:

SAE

forthebadge made-with-python
Python 3.6

The Steps under Feature Engineering are:

1. Handling Miisng Values

2. Outliers Detection

3. Feature Scaling/ Transformation

4. Feature Selection

5. Handling Imbalanced Data

Link To the YouTube Channel for Video Explanation of these techniques: KRISH NAIK SIR

My Kaggle Notebook Link: Harsh Jain

About

FEATURE ENGINEERING STEPS

Resources

Readme
Activity

Stars

2 stars

Watchers

1 watching

Forks

0 forks
Report repository

Releases

No releases published

Packages

No packages published

Languages