use AI::NeuralNet::Simple;
  my $net = AI::NeuralNet::Simple->new(2,1,2);
  # teach it logical 'or'
  for (1 .. 10000) {
      $net->train([1,1],[0,1]);
      $net->train([1,0],[0,1]);
      $net->train([0,1],[0,1]);
      $net->train([0,0],[1,0]);
  }
  printf "Answer: %d\n";,  $net->winner([1,1]);
  printf "Answer: %d\n",   $net->winner([1,0]);
  printf "Answer: %d\n",   $net->winner([0,1]);
  printf "Answer: %d\n\n", $net->winner([0,0]);

##</code><code>##

  $net->train([1,1], [0,1]);
  $net->train([1,0], [0,1]);
  $net->train([0,1], [0,1]);
  $net->train([0,0], [1,0]);

##</code><code>##

  for (1 .. 10000) {
    $net->train([1,1], [0,1]);
    $net->train([1,0], [0,1]);
    $net->train([0,1], [0,1]);
    $net->train([0,0], [1,0]);
  }

##</code><code>##

  $net->train_set([
    [1,1], [0,1],
    [1,0], [0,1],
    [0,1], [0,1],
    [0,0], [1,0],
  ], 10000);

##</code><code>##

  $net->iterations(100000); # let's have lots more iterations!
  $net->iterations;         # returns 100000
  my @training_data = (
    [1,1], [0,1],
    [1,0], [0,1],
    [0,1], [0,1],
    [0,0], [1,0],
  );
  $net->train_set(\@training_data);

##</code><code>##

  use Data::Dumper;
  print Dumper $net->infer([1,1]);

  $VAR1 = [
          '0.00993729281477686',
          '0.990100297418451'
        ];

##</code><code>##

  print $net->winner([1,1]); # will likely print "1"