7 Data Pre-Processing Methods With SciKit-Learn
Last Updated on July 26, 2023 by Editorial Team
Author(s): Carla Martins
Originally published on Towards AI.
Using Python and Google Colab
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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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