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.

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

• Guide to Encoding Categorical Features using Scikit-Learn for Machine Learning
• What is Feature Scaling & Why is it Important in Machine Learning?
• Stop Wasting Useful Information When Imputing Missing Values