7 Data Pre-Processing Methods With SciKit-Learn

Author(s): Carla Martins

Originally published on Towards AI.

Using Python and Google Colab

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Photo by James Harrison on Unsplash

Data pre-processing is an important part of preparing, organizing, and structuring data for further analysis or Machine Learning model engineering. This is a fundamental step that aims to organize the data so that it can be interpreted by the mathematical and computational models that we intend to apply.

The main problems encountered with data when not in ready-to-analyze format are generally related to data type (string vs float or int), different scales, outliers, different encoding, non-normal (or non-Gaussian) distribution, or presence of outliers.

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Published via Towards AI