<gh_stars>1-10
"""This script will tell simple neural network
training with forward pass method.
Assume we want to train and predict number of 7,8,9,10 into linear function f(x) = 3x + 2"""

import numpy as np

def forwardPass(inputs, weight, bias):
	w_sum = np.dot(inputs, weight) + bias
	
	# Linear Activation f(x) = x
	act = w_sum

	return act

# Pre-Trained Weights & Biases after Training
W = np.array([[2.99999928]])
b = np.array([1.99999976])

# Initialize Input Data
inputs = np.array([[7], [8], [9], [10]])

# Output of Output Layer
o_out = forwardPass(inputs, W, b)

print("Output Layer Output (Linear)")
print("============================")
print(o_out, "\n")

"""
The output will be
Output Layer Output (Linear)
============================
(array([[ 22.99999472],
       [ 25.999994  ],
       [ 28.99999328],
       [ 31.99999256]]), '\n')

The true math is 23,26,29,32 There was minimum error in calculation
"""
