Challenge: Creating a Neuron

Your task is to implement the basic structure of a single neuron by completing the missing parts of the code below.

Follow these steps carefully:

1. Initialize parameters:
   • Create the array of weights using np.random.uniform() with values in the range $[-1, 1)$.
   • Create a single bias value using the same uniform distribution.
   • Both should be initialized in the neuron's constructor (__init__).
2. Compute the neuron's input:
   • Inside the activate() method, calculate the weighted sum of the inputs using the dot product:

     np.dot(inputs, self.weights)
     

   • Add the bias to this sum and store the result in the variable input_sum_with_bias.
3. Apply the activation function:
   • Use the provided sigmoid() function to compute the neuron’s output from input_sum_with_bias.
   • Store the result in the variable output and return it.