Apache Spark Deep Learning Cookbook

How to do it...

This section walks through the steps to normalize the height and weight.

1. Slice the array into inputs and outputs using the following script:

X = data_array[:,:2]y = data_array[:,2]

2. The mean and the standard deviation can be calculated across the 29 individuals using the following script:

x_mean = X.mean(axis=0)x_std = X.std(axis=0)

3. Create a normalization function to normalize X using the following script:

 def normalize(X):     x_mean = X.mean(axis=0)     x_std = X.std(axis=0)     X = (X - X.mean(axis=0))/X.std(axis=0)     return X