Scaling the input dataset

Scaling a dataset is a process where we limit the variables within a dataset to ensure they do not have a very wide range of different values. One way to achieve this is to divide each variable in the dataset by the maximum value of the variable. Typically, neural networks perform well when we scale the input datasets.

In this section, let's understand the reason neural networks perform better when the dataset is scaled.

Getting ready

To understand the impact of the scaling input on the output, let's contrast the scenario where we check the output when the input dataset is not scaled, with the output when the input dataset is scaled.

Input data is not scaled:

In the preceding table, note...