Implement the Neuron class, which will have several methods: __init__. It takes as input an array of neuron weights --- w=(w1,…,wn) , as well as an activation function f (by default, f(x)=x ). Stores the weights and the function inside the class. forward. It takes as input an array x=(x1,…,xN) --- neuron inputs. Returns f(w1x1+…+wnxn) . backlog. Returns the last array x that was passed to the forward function. class Neuron: def __init__(self, w, f = lambda x: x): #YOUR CODE HERE def forward(self, x): #YOUR CODE HERE def backlog(self): #YOUR CODE HERE

# Define the neuron class with two methods:
class Neuron:

    def __init__(self, w, f = lambda x: x):
        self.w = w
        self.f = f

    def forward(self, x):
        """
        Calculates neuron output
        """
        # Your code here
        return self.f(np.dot(self.w,x))
    
    def backlog(self):
        return self.x