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Numerical Variables

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In this course, you will learn how to apply basic and more advanced feature engineering to tabular data with python, during this course,  we will see a range of different techniques and methods to handle many common cases within the data set, so in result, you will create great features so that your machine learning models can predict good results.

Feature Engineering with Python

## Definition

Another technique you can use to handle outliers is applying some mathematical transformations like log transformation. 

We went through various methods in the variable transformation section, and you can choose one that is more suitable for your data.

As a reminder, here are the different methods you can apply:

- Logarithm Transformation
- Square Transformation
- Reciprocal Transformation
- Exponential or Power Transformation
- Box-Cox Transformation
- Yeo-Johnson Transformation

Here is an example doing the log transformation:

# Definition

Another technique you can use to handle outliers is applying some mathematical transformations like log transformation. 

We went through various methods in the variable transformation section, and you can choose one that is more suitable for your data.

As a reminder, here are the different methods you can apply:

- Logarithm Transformation
- Square Transformation
- Reciprocal Transformation
- Exponential or Power Transformation
- Box-Cox Transformation
- Yeo-Johnson Transformation

Here is an example doing the log transformation:

We saw many transformation functions previously to apply on numerical variables, and those functions can be performed as an act of engineering outliers; in this lesson, we will learn how to do that.


Introduction

Variable Types

Common Concerns in Datasets

Handling & Imputing Missing Values

Encoding Categorical Variables

Transforming Variables

Variable Discretization

Handling Outliers

Feature Scaling

Engineering Geospatial Data

Handling Date-Time and Mixed Variables

Resampling Imbalanced Data

Advanced Feature Engineering Techniques

Conclusion

Transformation

Definition