Scaling data to the standard normal
A preprocessing step that is almost recommended is to scale columns to the standard normal. The standard normal is probably the most important distribution of all statistics.
If you've ever been introduced to statistics, you must have almost certainly seen z-scores. In truth, that's all this recipe is about—transforming our features from their endowed distribution into z-scores.
The act of scaling data is extremely useful. There are a lot of machine learning algorithms, which perform differently (and incorrectly) in the event the features exist at different scales. For example, SVMs perform poorly if the data isn't scaled because it uses a distance function in its optimization, which is biased if ...