// http://codingtra.in

​

// XOR

// https://youtu.be/188B6k_F9jU

​

// Neural Network Library

// https://github.com/CodingTrain/Toy-Neural-Network-JS

​

let nn;

let lr_slider;

​

let training_data = [{

    inputs: [0, 0],

    outputs: [0]

  },

  {

    inputs: [0, 1],

    outputs: [1]

  },

  {

    inputs: [1, 0],

    outputs: [1]

  },

  {

    inputs: [1, 1],

    outputs: [0]

  }

];

​

function setup() {

  createCanvas(400, 400);

  nn = new NeuralNetwork(2, 4, 1);

  lr_slider = createSlider(0.01, 0.5, 0.1, 0.01);

​

}

​

function draw() {

  background(0);

​

  for (let i = 0; i < 100; i++) {

    let data = random(training_data);

    nn.train(data.inputs, data.outputs);

  }

​

  nn.setLearningRate(lr_slider.value());

​

  let resolution = 10;

  let cols = width / resolution;

  let rows = height / resolution;

  for (let i = 0; i < cols; i++) {

    for (let j = 0; j < rows; j++) {

      let x1 = i / cols;

      let x2 = j / rows;

      let inputs = [x1, x2];

      let y = nn.predict(inputs);

      noStroke();

      fill(y * 255);

      rect(i * resolution, j * resolution, resolution, resolution);

    }

  }

​

​

​

}