# Implementation of Delta Learning Algorithm in Python: Delta Learning Algorithm Code in Python Implementation of Delta Learning Algorithm in Python: Delta Learning Algorithm Code in Python

What is the Delta Learning Algorithm?

It is a specific type of backpropagation which is used to make the connections between input and output with the layers of artificial neurons.
It is also called a delta rule.

Code:

from math import exp

def mul(l1, l2):    return round(sum(a*b for a,b in zip(l1, l2)), 3)

def sgn(x):   return 1 if x > 0 else -1

def imul(x, a):   return [round(a*xi,3) for xi in x]

def add(l1, l2):    return [round(a+b,3) for a,b in zip(l1, l2)]

def func(net):    return 2 / (1 + exp(-net)) - 1

def funcdash(o):   return (1 - o*o)/2

if __name__ == '__main__':

c = 0.1

n = int(input('Enter no of input:'))

xn, dn = [], []

for i in range(n):

xi  = list(map(float, input(f'Enter x{i}: ').strip().split(' '))) di = int(input('Enter desired output:'))

xn.append(xi); dn.append(di)

w = list(map(float, input('Enter initial weights:').split(' ')))

for xi, di in zip(xn, dn):

net = mul(w, xi); oi = round(func(net), 3)

fnetdash = round(funcdash(oi), 3); print(f'oi = {oi}, fnetdash = {fnetdash}')

xi = imul(xi, c * (di - oi) * fnetdash);   w = add(w, xi)

print(f'Updated weight: {w}')

Note: Plz insert indentations wherever required.