Building a single layer neural network

Now that we know how to create a perceptron, let's create a single layer neural network. A single layer neural network consists of multiple neurons in a single layer. Overall, we will have an input layer, a hidden layer, and an output layer.

How to do it…

1. Create a new Python file, and import the following packages:

   import numpy as np
   import matplotlib.pyplot as plt
   import neurolab as nl 

2. We will use the data in the data_single_layer.txt file. Let's load this:

   # Define input data
   input_file = 'data_single_layer.txt'
   input_text = np.loadtxt(input_file)
   data = input_text[:, 0:2]
   labels = input_text[:, 2:]

3. Let's plot the input data:

   # Plot input data
   plt.figure()
   plt.scatter(data[:,0], data[:,1])
   plt.xlabel('X-axis')
   plt.ylabel('Y-axis')
   plt.title('Input data')

4. Let's extract the minimum and maximum values:

   # Min and max values for each dimension
   x_min, x_max = data[:,0].min(), data[:,0].max()
   y_min...