diff --git a/README.md b/README.md
index 642836c..3daa4e3 100644
--- a/README.md
+++ b/README.md
@@ -10,30 +10,40 @@ The version `1.0.0` includes just basic Neural Network functions such as Feed Fo
 A simple Feed Forward Neural Network can be constructed and trained as follows:
 
 ```go
-// set the random seed to 0
-rand.Seed(0)
-
-// create the XOR representation patter to train the network
-patterns := [][][]float64{
-  {{0, 0}, {0}},
-  {{0, 1}, {1}},
-  {{1, 0}, {1}},
-  {{1, 1}, {0}},
+package main
+
+import (
+	"github.com/goml/gobrain"
+	"math/rand"
+)
+
+func main() {
+	// set the random seed to 0
+	rand.Seed(0)
+
+	// create the XOR representation patter to train the network
+	patterns := [][][]float64{
+		{{0, 0}, {0}},
+		{{0, 1}, {1}},
+		{{1, 0}, {1}},
+		{{1, 1}, {0}},
+	}
+
+	// instantiate the Feed Forward
+	ff := &gobrain.FeedForward{}
+
+	// initialize the Neural Network;
+	// the networks structure will contain:
+	// 2 inputs, 2 hidden nodes and 1 output.
+	ff.Init(2, 2, 1)
+
+	// train the network using the XOR patterns
+	// the training will run for 1000 epochs
+	// the learning rate is set to 0.6 and the momentum factor to 0.4
+	// use true in the last parameter to receive reports about the learning error
+	ff.Train(patterns, 1000, 0.6, 0.4, true)
 }
 
-// instantiate the Feed Forward
-ff := &gobrain.FeedForward{}
-
-// initialize the Neural Network;
-// the networks structure will contain:
-// 2 inputs, 2 hidden nodes and 1 output.
-ff.Init(2, 2, 1)
-
-// train the network using the XOR patterns
-// the training will run for 1000 epochs
-// the learning rate is set to 0.6 and the momentum factor to 0.4
-// use true in the last parameter to receive reports about the learning error
-ff.Train(patterns, 1000, 0.6, 0.4, true)
 ```
 
 After running this code the network will be trained and ready to be used.