Day 82

Deep Learning_day5
Fri, Sep 01, 2023

<Deep Neural Network>

class AffineFunction:
	def __init__(self, w, b):
		self.w = w
        self.b = b
    def forward(self, x):
    	z = np.dot(self.w, x) + self.b
        return z
        
class Sigmoid:
	def forward(self, z):
    	y = 1 / (1 + np.exp(-z))
        return y
        
class Artificial Neuron:
	def __init__(self, w, b):
    	self.affine = AffineFunction(w=w, b=b)
        self.activation = Sigmoid()
    def forward(self, x):
    	z = self.affine.forward(x)
        y = self.activation.forward(z)
        return y

# NN(Neural Network)
class Model:
	def __init__(self):
    	self.AND = ArtificialNeuron([5, 5], -7.5)
        self.NAND = ArtificialNeuron([-5, -5], 7.5)
        self.OR = ArtificialNeuron([5, 5], -2.5)
        
    # Hidden Layer
	def forward(self, x):
    	a1 = self.AND.forawrd(x)
        a2 = self.OR.forward(x)
        a3 = self.NAND.forward(x)
        
        a = np.array([a1, a2, a3])
        return a
        
  x = [0, 1]
  model = Model()
  a = model.forward(x)
  print(f'x: {x}')
  print(f'a: {a}')