Using Standard Scaler to scale features | Machine Learning

In this tutorial, we'll look at Standard Scaler, a type of feature scaling technique for linear Machine Learning models.

In the tutorial, we'll be going through all the nitty-gritties of Standard Scaler, when to use them, when NOT to use them, how is it helpful, how is it NOT so helpful etc etc.

0:00 Intro
3:10 Python code

Feature scaling is so important that your model performance could shoot up by many a percentage points if you use the correct feature scaling techniques.

In a nutshell, Standard Scaler works by subtracting the mean, and dividing by the standard deviation for each observation in a particular feature so as to give it the properties of a Gaussian "bell-shaped" curve.

I've uploaded all the relevant code and datasets used here (and all other tutorials for that matter) on my github page which is accessible here:

Link:

https://github.com/rachittoshniwal/machineLearning

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Тэги:

#standard_scaler #feature_engineering #machine_learning #data_science #python #easy #gaussian #bell_curve

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