Simple deep learning example (node + weight + relu)

deep_example.py

import numpy as np
from sys import argv


def relu(input_value):
    output_value = max(0, input_value)
    return output_value

children = int(argv[1])
accounts = int(argv[2])

input_data = np.array([children, accounts])

weights = {
    'node_0': np.array([2, 4]),
    'node_1': np.array([4, -5]),
    'output': np.array([2, 7])
}

node_0_input = (input_data * weights['node_0']).sum()
node_1_input = (input_data * weights['node_1']).sum()

node_0_output = relu(node_0_input)
node_1_output = relu(node_1_input)

hidden_layer_values = np.array([node_0_output, node_1_output])

input_final_layer = (hidden_layer_values * weights['output']).sum()
output = relu(input_final_layer)

print(output)

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