https://github.com/petrbroz/simple-neural-network

Stupid simple implementation of a fully-connected artificial neural network for learning purposes.
https://github.com/petrbroz/simple-neural-network

Last synced: 3 months ago
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Stupid simple implementation of a fully-connected artificial neural network for learning purposes.

• Host: GitHub
• URL: https://github.com/petrbroz/simple-neural-network
• Owner: petrbroz
• Created: 2024-05-21T10:38:28.000Z (over 1 year ago)
• Default Branch: master
• Last Pushed: 2024-05-21T10:39:14.000Z (over 1 year ago)
• Last Synced: 2025-05-16T00:18:44.402Z (5 months ago)
• Language: TypeScript
• Size: 6.84 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# simple-neural-network

Stupid simple implementation of a fully-connected artificial neural network for learning purposes. Based on various online resources, incl. https://www.youtube.com/watch?v=sIX_9n-1UbM.

> Note however that there seems to be a small error in the YouTube video. Around the 3:58 time mark a derivative of the cost function $(\hat{a_1} - a_1^{(4)})^2$ is said to be $2(\hat{a_1} - a_1^{(4)})$ while it should be $2(a_1^{(4)} - \hat{a_1})$.

## Usage

```js

// Create neural network with specific number of layers and neurons,

// in this case with an input layer of 2 neurons, one hidden layer of 2 neurons, and an output layer of 1 neuron

const network = new NeuralNetwork([2, 2, 1]);

// Repeatedly train the network with 0.25 learning rate

const trainingData = [

    { input: [0.0, 0.0], output: [1.0] },

    { input: [0.0, 1.0], output: [0.0] },

    { input: [1.0, 0.0], output: [0.0] },

    { input: [1.0, 1.0], output: [1.0] }

];

for (let i = 0; i < 1000; i++) {

    network.train(trainingData, 0.25);

}

// Test

for (let y = 0.0; y <= 1.0; y += 0.1) {

    for (let x = 0.0; x <= 1.0; x += 0.1) {

        console.log(network.predict([x, y]));

    }

}

```