Neural Network Data Normalization and Encoding

A topic that’s often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, which can be male or female) and categorical data (such as a community, which can be suburban, city or rural) must be encoded in numeric form. Additionally, experience has shown that in most cases numeric data, such as a person’s age, should be normalized. There are many references that discuss the theory of normalization and encoding, but few that provide practical guidance and even fewer that provide code-implementation examples. This article explains how to normalize and encode neural network data from a developer’s point of view. The process is conceptually simple but surprisingly difficult to implement.