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Feature Engineering Techniques

An introduction to some of the main techniques which can be used in order to prepare raw features for Machine Learning analysis.

Pier Paolo Ippolito
Towards Data Science
8 min readNov 15, 2019

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Introduction

Feature Engineering is one of the most important steps to complete before starting a Machine Learning analysis. Creating the best possible Machine Learning/Deep Learning model can certainly help to achieve good results, but choosing the right features in the right format to feed in a model can by far boost performances leading to the following benefits:

  • Enable us to achieve good model performances using simpler Machine Learning models.
  • Using simpler Machine Learning models, increases the transparency of our model, therefore making easier for us to understand how is making its predictions.
  • Reduced need to use Ensemble Learning techniques.
  • Reduced need to perform Hyperparameters Optimization.

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Towards Data Science
Towards Data Science

Published in Towards Data Science

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Pier Paolo Ippolito
Pier Paolo Ippolito

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