code: import numpy as np
  
  # Mini Dataset
  input_data = np.array([5, 7, 8, 1])
  
  weights = {'node0': np.array([1, 1]),
             'node1': np.array([-1, 1]),
             'output': np.array([2, -1])}
  
  
  # Activation Function
  def ReLu(x):
      out = max(0, x)
      return out
  
  
  def predict_with_NN(input_data_row, weights):
      print("\nFirst element of input data: %s" % input_data)
      print("Weights for nodes in hidden layer 0: %s" % weights['node0'])
      print("Weights for nodes in hidden layer 1: %s" % weights['node1'])
      print("Weights for nodes in output: %s" % weights['output'])
  
      # Calculation for node 0 value
      node_0_input = (input_data_row * weights['node0']).sum()
      print("Node 0 in hidden layer before activation function: %d" % node_0_input)
      node_0_output = ReLu(node_0_input)
      print("Node 0 in hidden layer after activation function: %d" % node_0_output)
  
      # Calculation for node 1 value
      node_1_input = (input_data_row * weights['node1']).sum()
      print("Node 1 in hidden layer before activation function: %d" % node_1_input)
      node_1_output = ReLu(node_1_input)
      print("Node 1 in hidden layer after activation function: %d" % node_1_output)
  
      # put node values into array : hidden_layer_output
      hidden_layer_output = np.array([node_0_output, node_1_output])
      print("Hidden layer: %s" % hidden_layer_output)
  
      # Calculate model output
      input_to_final_layer = (hidden_layer_output * weights['output']).sum()
      print("Output layer before activation function: %d" % input_to_final_layer)
      model_output = ReLu(input_to_final_layer)
      print("Output layer after activation function: %d" % model_output)
  
      # Return model output
      return model_output
  
  
  # Create Empty list to store prediction results
  results = []
  for input_data_row in input_data:
      # Append prediction to result
      results.append(predict_with_NN(input_data_row, weights))
  
  
  print(results)
  
  
  
apis: numpy.array