April 2018
Beginner to intermediate
282 pages
6h 52m
English
As you may have noticed, features are scaled in the previous section before training machine learning algorithms. Feature transformations are usually necessary for ML algorithms to work properly. For example, as a rule of thumb, for ML algorithms that use regularization, normalization is usually applied to features.
The following is a list of use cases where you should transform your features to prepare your dataset to be ready for ML algorithms: