Apache Spark Deep Learning Cookbook

How to do it...

This section walks through the steps to visualize all of the predicted points in a graph.

1. Compute the minimum and maximum points of the graph  using the following script:

x_min = min(data_array[:,0])-0.1x_max = max(data_array[:,0])+0.1y_min = min(data_array[:,1])-0.1y_max = max(data_array[:,1])+0.1increment= 0.05print(x_min, x_max, y_min, y_max)

2. Generate x and y values in increments of 0.05 units and then create an array called xy_data, as seen in the following script:

x_data= np.arange(x_min, x_max, increment)y_data= np.arange(y_min, y_max, increment)xy_data = [[x_all, y_all] for x_all in x_data for y_all in y_data]

3. Finally, a similar script to that used earlier in the chapter is used to generate a gender score and populate ...