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Tutorial on how to perform feature encoding, feature scaling, and missing values imputation using the scikit-learn library

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Scikit-learn Tutorial

Introduction

Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting and k-means and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

Repository description

This repository contains 3 separate notebooks, each covering different aspects of data preprocessing for machine learning using scikit-learn, namely:

  • Feature encoding
  • Feature scaling
  • Missing values imputation

Medium (Towards Data Science) articles

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Tutorial on how to perform feature encoding, feature scaling, and missing values imputation using the scikit-learn library

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