When you're working with a learning model, it is important to scale the features to a range which is centered around zero. This is done so that the variance of the features are in the same range. If a feature's variance is orders of magnitude more than the variance of other features, that particular feature might dominate other features in the dataset, which is not something we want happening in our model. The aim here is to to achieve Gaussian with zero mean and unit variance. There are many ways of doing this, two most popular are standardisation and normalisation. No matter which method you choose, the SciKit Learn library provides a class to easily scale our data. We can use the StandardScaler