import "github.com/sivamgr/go-neural"

  //...

  // Network has 9 enters and 3 layers 
  // ( 9 neurons, 9 neurons and 4 neurons).
  // Last layer is network output.
  n := neural.NewNetwork(9, []int{9,9,4})
  // Randomize sypaseses weights
  n.RandomizeSynapses()
  
  result := n.Calculate([]float64{0,1,0,1,1,1,0,1,0})
  

  import "github.com/sivamgr/go-neural/persist"

  persist.ToFile("/path/to/file.json", network)

  import "github.com/sivamgr/go-neural/persist"

  network := persist.FromFile("/path/to/file.json")

  import "github.com/sivamgr/go-neural/learn"

  var input, idealOutput []float64
  // Learning speed [0..1]
  var speed float64

  learn.Learn(network, in, idealOut, speed)

  e := learn.Evaluation(network, in, idealOut)

	network := neural.NewNetwork(2, []int{2, 2})
	engine := New(network)
	engine.Start()

	engine.Learn([]float64{1, 2}, []float64{3, 3}, 0.1)

	out := engine.Calculate([]float64{1, 2})