<reponame>Jayasagar/neural-networks-and-fundamentals
import numpy as np
'''
Requirment: Decide whether to attend festival at home town ot not

Criteria 1: Weather rainy or not
Criteria 2: Can I go by train?
Criteria 3: Will I get leave in office?

Bias: If leave has more bias value then, others not taking any priority
Leave  = 6

Bias : If All have equal priority, then bias will be less
'''

inputs = [1, 0, 1] # inputs[weather, train, leave]
weights = [2, 2, 6] # weights[weather, train, leave]

def perceptron(inputs, weights, bias):
    productAndSumOfInputsWeight = (inputs * weights).sum()
    print ('Product Array:', productAndSumOfInputsWeight)

    if productAndSumOfInputsWeight + (-bias) <= 0:
        return 0
    return 1


print('Am I going to Festival:', perceptron(np.array(inputs), np.array(weights), 5))
import numpy as np
'''
Requirment: Decide whether to attend festival at home town ot not

Criteria 1: Weather rainy or not
Criteria 2: Can I go by train?
Criteria 3: Will I get leave in office?

Bias: If leave has more bias value then, others not taking any priority
Leave  = 6

Bias : If All have equal priority, then bias will be less
'''

inputs = [1, 0, 1] # inputs[weather, train, leave]
weights = [2, 2, 6] # weights[weather, train, leave]

def perceptron(inputs, weights, bias):
    productAndSumOfInputsWeight = (inputs * weights).sum()
    print ('Product Array:', productAndSumOfInputsWeight)

    if productAndSumOfInputsWeight + (-bias) <= 0:
        return 0
    return 1


print('Am I going to Festival:', perceptron(np.array(inputs), np.array(weights), 5))
Requirment: Decide whether to attend festival at home town ot not  Criteria 1: Weather rainy or not Criteria 2: Can I go by train? Criteria 3: Will I get leave in office?  Bias: If leave has more bias value then, others not taking any priority Leave  = 6  Bias : If All have equal priority, then bias will be less # inputs[weather, train, leave] # weights[weather, train, leave]