[Python] 딥러닝 - 인공신경망(ANN)

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# 퍼셉트론 AND 게이트 구현
import numpy as np
def AND(x1,x2) : 
    x = np.array([x1,x2]) # 입력값
    w = np.array([0.5, 0.5]) # 가중치
    b = -0.8 # 편향
    tmp = np.sum(w*x) + b 
    if tmp <= 0 : 
        return 0
    else : 
        return 1

for xs in [(0, 0), (0, 1), (1, 0), (1, 1)] :
    y = AND(xs[0], xs[1])
    print(xs, "=>", y)

# 퍼셉트론 OR 게이트 구현
def OR(x1,x2) : 
    x = np.array([x1,x2]) # 입력값
    w = np.array([0.5, 0.5]) # 가중치
    b = -0.2 # 편향
    tmp = np.sum(w*x) + b 
    if tmp <= 0 : 
        return 0
    else : 
        return 1

for xs in [(0, 0), (0, 1), (1, 0), (1, 1)] :
    y = OR(xs[0], xs[1])
    print(xs, "=>", y)

# 퍼셉트론 NAND 게이트 구현    
def NAND(x1,x2) : 
    x = np.array([x1,x2]) # 입력값
    w = np.array([-0.5, -0.5]) # 가중치
    b = 0.8 # 편향
    tmp = np.sum(w*x) + b 
    if tmp <= 0 : 
        return 0
    else : 
        return 1

for xs in [(0, 0), (0, 1), (1, 0), (1, 1)] :
    y = NAND(xs[0], xs[1])
    print(xs, "=>", y)