Perceptron inference

perceptron-inference.py

def activation(x, function_name):
    if function_name == 'step':
        return step(x)
    elif function_name == 'sign':
        return sign(x)
    else:
        raise NotImplementedError
    
    
def initialize_weights(num_columns):
    return np.zeros(num_columns)
    
    
def predict(vector, weights, activation_function):    
    linear_sum = np.dot(weights, vector)
    output = activation(linear_sum, activation_function)
    return output