Useful Links

• "Simple" Description of Neural Networks
• Neural Network Basics
• The Role of Bias in Neural Networks

Creating a Neuron

let Neuron = require('@liquid-carrot/carrot').Neuron

let n = new Neuron()

Activating a Neuron

let Neuron = require('@liquid-carrot/carrot').Neuron

let n = new Neuron()

n.activate(Math.random(), function(error, results) {
  console.log(results) // 0.4254387327
})

Teaching a Neuron

let Neuron = require('@liquid-carrot/carrot').Neuron

let n = new Neuron()

n.propagate(0, function(error, fault) {
  console.log(results) // 0.124511366
})

Connecting two Neurons

let Neuron = require('@liquid-carrot/carrot').Neuron

let n0 = new Neuron()
let n1 = new Neuron()

n0.project(n1, function(error, connection) {
  console.log(connection)
})

new Neuron()

• new Neuron(): Creates a new neuron.
• new Neuron({ inputs: [n0, n1], outputs: [n2] }): Creates a new neuron with n0 and n1 as incoming connections, and n2 as an outgoing connection.
• new Neuron(n0): Creates a new neuron with the same connections as n0

.is.input([callback])

• neuron.is.input(): Returns true if neuron has no incoming connections; Invokes callback(error, isInput)

.is.output([callback])

• neuron.is.output(): Returns true if neuron has no outgoing connections; Invokes callback(error, isOutput)

.project(object[, callback])

• neuron.project(other_neuron): Connects neuron to other_neuron; Invokes callback(error, connections)
• neuron.project(layer): Connects neuron to every neuron in layer; Invokes callback(error, connections)
• neuron.project(group): Connects neuron to every neuron in group; Invokes callback(error, connections)

.activate(inputs[,callback])

• .activate([0, 1, 0, 1]): Activates neuron with the given inputs; inputs.length must equal connections.length; Invokes callback(error, results)

.propagate(feedback[,callback])

• .propagate([1, 0, 1, 0]): Calculates incoming connection errors; Invokes callback(error, results)