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

Neural Network JavaScript library for Coding Train tutorials
https://github.com/CodingTrain/Toy-Neural-Network-JS

Last synced: 3 months ago
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Neural Network JavaScript library for Coding Train tutorials

Host: GitHub
URL: https://github.com/CodingTrain/Toy-Neural-Network-JS
Owner: CodingTrain
License: mit
Created: 2018-02-02T17:50:25.000Z (almost 7 years ago)
Default Branch: master
Last Pushed: 2023-03-27T10:25:43.000Z (over 1 year ago)
Last Synced: 2024-05-01T09:38:36.951Z (7 months ago)
Language: JavaScript
Size: 13 MB
Stars: 420
Watchers: 33
Forks: 241
Open Issues: 63
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # Toy-Neural-Network-JS

![ci](https://github.com/CodingTrain/Toy-Neural-Network-JS/actions/workflows/ci.yml/badge.svg)

Neural Network JavaScript library for Coding Train tutorials

## Examples / Demos

Here are some demos running directly in the browser:

* [XOR problem](https://codingtrain.github.io/Toy-Neural-Network-JS/examples/xor/), [Coding Challenge on YouTube](https://www.youtube.com/watch?v=188B6k_F9jU)

* [Handwritten digit recognition](https://codingtrain.github.io/Toy-Neural-Network-JS/examples/mnist/)

* [Doodle classifier](https://codingtrain.github.io/Toy-Neural-Network-JS/examples/doodle_classification/), [Coding Challenge on YouTube](https://www.youtube.com/watch?v=pqY_Tn2SIVA&list=PLRqwX-V7Uu6Zs14zKVuTuit6jApJgoYZQ)

## To-Do List

* [x] Redo gradient descent video about

* [x] Delta weight formulas, connect to "mathematics of gradient" video

* [x] Implement gradient descent in library / with code

* [x] XOR coding challenge [live example](https://codingtrain.github.io/Toy-Neural-Network-JS/examples/xor/)

* [ ] MNIST coding challenge [live example](https://codingtrain.github.io/Toy-Neural-Network-JS/examples/mnist/)

    * redo this challenge

    * cover softmax activation, cross-entropy

    * graph cost function?

    * only use testing data

* [ ] Support for saving / restoring network (see [#50](https://github.com/CodingTrain/Toy-Neural-Network-JS/pull/50))

* [ ] Support for different activation functions (see [#45](https://github.com/CodingTrain/Toy-Neural-Network-JS/pull/45), [#62](https://github.com/CodingTrain/Toy-Neural-Network-JS/pull/62))

* [ ] Support for multiple hidden layers (see [#61](https://github.com/CodingTrain/Toy-Neural-Network-JS/pull/61))

* [ ] Support for neuro-evolution

    * [ ] play flappy bird (many players at once).

    * [ ] play pong (many game simulations at once)

    * [ ] steering sensors (a la Jabril's forrest project!)

* [ ] Combine with ml5 / deeplearnjs

## Getting Started

If you're looking for the original source code to match the videos [visit this repo](https://github.com/CodingTrain/Rainbow-Code/tree/master/Courses/natureofcode/10.18-toy_neural_network)

### Prerequisites

You need to have the following installed:

1. Nodejs

2. NPM

3. Install the NodeJS dependencies via the following command:

```

npm install

```

### Installing

This Project doesn't require any additional Installing steps

### Documentation

* `NeuralNetwork` - The neural network class

  * `predict(input_array)` - Returns the output of a neural network

  * `train(input_array, target_array)` - Trains a neural network

## Running the tests

The Tests can either be checked via the automatically running CircleCI Tests or you can also run `npm test` on your PC after you have done the Step "Prerequisites"

## Built With

* [Nodejs](https://nodejs.org/) - The code language used

* [CircleCI](https://circleci.com/) - Automated Test Service

* [Jest](https://facebook.github.io/jest/) - Testing Framework used

## Contributing

Please send PullRequests. These need to pass a automated Test first and after it will get reviewed and on that review either denied or accepted.

## Libraries built by the community

Here are some libraries with the same or similar functionality to this one built by the community:

- [Java Neural Network Library](https://github.com/kim-marcel/basic_neural_network) by [kim-marcel](https://github.com/kim-marcel)

- [Library-less Java Neural Network](https://github.com/Fir3will/Java-Neural-Network) by [Fir3will](https://github.com/Fir3will)

- [Python Neural Network Library](https://github.com/Gabriel-Teston/Machine-Learning) by [Gabriel-Teston](https://github.com/Gabriel-Teston)

- [Python Neural Network Library](https://github.com/GypsyDangerous/simple-deep-neural-network/blob/master/README.md) by [David Snyder](https://github.com/GypsyDangerous)

- [JavaScript Multi-Layer Neural Network Library](https://github.com/notshekhar/neuralnet) by [Shekhar Tyagi](https://github.com/notshekhar)

- [F# Neural Network Library](https://github.com/jackroi/NeuralNetwork-fsharp) by [jackroi](https://github.com/jackroi)

- [TinyNeuralNetwork4Java](https://github.com/anirudhgiri/TinyNN4J) by [Anirudh Giri](https://github.com/anirudhgiri)

- [miniANN Neural Network Library JavaScript](https://github.com/savvysiddharth/mini-ANN-js) by [Siddharth Maurya](https://github.com/savvysiddharth)

- [Convolutional Neural Network Library JavaScript](https://github.com/therealyubraj/CNN_JS) by [Yubraj Sharma](https://github.com/therealyubraj)

Feel free to add your own libraries.

## Versioning

We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/CodingTrain/Toy-Neural-Network-JS/tags).

## Authors

* **shiffman** - *Initial work* - [shiffman](https://github.com/shiffman)

See also the list of [contributors](https://github.com/CodingTrain/Toy-Neural-Network-JS/contributors) who participated in this project.

## License

This project is licensed under the terms of the MIT license, see LICENSE.