input: Write a python function to create a neuron with random weights and process given inputs using the neuron class.
  assert abs(Neuron(3).process([1, -1, 0.5]) - 0.5) < 0.5
  assert abs(Neuron(2).process([0.25, -0.75]) - 0.5) < 0.5
  assert abs(Neuron(4).process([0.1, 0.2, 0.3, 0.4]) - 0.5) < 0.5
output: import random
  import math
  
  class Neuron:
      def __init__(self, num_inputs):
          self.weights = [random.uniform(-1, 1) for _ in range(num_inputs)]
          self.bias = random.uniform(-1, 1)
  
      def process(self, inputs):
          activation = sum(w * i for w, i in zip(self.weights, inputs)) + self.bias
          return 1 / (1 + math.exp(-activation))
  
  # Example usage:
  # neuron = Neuron(3)
  # output = neuron.process([1, -1, 0.5])