Feature Scaling Data with Scikit-Learn for Machine Learning in Python

Preprocessing data is an often overlooked key step in Machine Learning. In fact - it's as important as the shiny model you want to fit with it. You can have the best model crafted for any sort of problem - if you feed it garbage, it'll spew out garbage. It's worth noting that "garbage" doesn't refer to random data. It's a harsh label we attach to any data that doesn't allow the model to do its best - some more so than other.