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🥕 Evolutionary Neural Networks in JavaScript
| Date | Stars |
|---|---|
| 2026-07-31 | 292 |
| 2026-08-04 | 292 |
| 2026-08-05 | 292 |
| 2026-08-06 | 292 |
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<p align="center">
<img src="https://raw.githubusercontent.com/liquidcarrot/carrot/master/images/carrot-logo_readme.png" alt="Carrot Logo" width="600px"/>
</p>
<p align="center">
<a href="https://travis-ci.org/liquidcarrot/carrot">
<img src="https://travis-ci.org/liquidcarrot/carrot.svg?branch=master"
alt="Build Status via Travis CI">
</a>
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<img src="https://api.codacy.com/project/badge/Grade/3ee723b170f14b4990c8a0a6fc1feb27"
alt="Codacy Badge">
</a>
<a href="https://coveralls.io/github/liquidcarrot/carrot?branch=master">
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alt="Coverage Status">
</a>
<a href="https://discord.gg/P4FJG8rEYC">
<img src="https://img.shields.io/discord/800482235852914698" alt="Join the chat on Discord at https://discord.gg/P4FJG8rEYC">
</a>
<a href="/LICENSE">
<img src="https://img.shields.io/badge/License-MIT-blue.svg"
alt="Carrot's License">
</a>
<a href="https://github.com/liquidcarrot/carrot/issues">
<img src="https://img.shields.io/badge/Made%20with%20%E2%99%A5%20by-Liquid%20Carrot-ff1414.svg"
alt="Made with love">
</a>
</p>
<h4>ℹ️ The new TypeScript version is coming! If you would like to try the expiremental version please clone the repository and checkout the typescript branch of the project. Docs for this new version can temporarily be found <a href="https://raimannma.github.io/carrot/index.html">here</a></h4>
<p>
Carrot is an architecture-free neural network library built around neuroevolution
</p>
<p>
Why / when should I use this?
Whenever you have a problem that you:
- Don't know how-to solve
- Don't want to design a custom network for
- Want to discover the ideal neural-network structure for
You can use Carrot's ability to **design networks of arbitrary complexity by itself** to solve whatever problem you have. If you want to see Carrot designing a neural-network to play flappy-bird [check here](https://liquidcarrot.io/example.flappy-bird/)
</p>
For Documentation, visit [here](https://liquidcarrot.github.io/carrot)
## Key Features
- [Simple docs](https://liquidcarrot.github.io/carrot) & [interactive examples](https://liquidcarrot.io/example.flappy-bird/)
- **Neuro-evolution** & population based training
- Multi-threading & GPU (coming soon)
- Preconfigured GRU, LSTM, NARX Networks
- Mutable Neurons, Layers, Groups, and Networks
- SVG Network Visualizations using D3.js
## Demos
<br>
[Flappy bird neuro-evolution](https://liquidcarrot.io/example.flappy-bird/ "flappy bird playground")
## Install
```bash
$ npm i @liquid-carrot/carrot
```
Carrot files are hosted by JSDelivr
For prototyping or learning, use the latest version here:
```html
<script src="https://cdn.jsdelivr.net/npm/@liquid-carrot/carrot/dist/carrot.umd2.min.js"></script>
```
For production, link to a specific version number to avoid unexpected breakage from newer versions:
```html
<script src="https://cdn.jsdelivr.net/npm/@liquid-carrot/[email protected]/dist/carrot.umd2.min.js"></script>
```
## Getting Started
💡 Want to be super knowledgeable about neuro-evolution in a few minutes?
Check out [this article](https://www.oreilly.com/radar/neuroevolution-a-different-kind-of-deep-learning/ "Neuro-evolution based deep learning") by the creator of NEAT, Kenneth Stanley
💡 Curious about how neural-networks can understand speech and video?
Check out [this video on Recurrent Neural Networks](https://www.youtube.com/watch?v=LHXXI4-IEns), from [@LearnedVector](https://github.com/LearnedVector), on YouTube
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:9be07272df3afc3f, llm:Topics: lstm, neat, neural-networks, neuro-evolution, recurrent-neural-networks, machine-learning, javascript; description: 'Evolutionary Neural Networks in JavaScript' and README stating 'architecture-free neural network library built around neuroevolution'.
matched fp:9be07272df3afc3f, llm:Topics: lstm, neat, neural-networks, neuro-evolution, recurrent-neural-networks, machine-learning, javascript; description: 'Evolutionary Neural Networks in JavaScript' and README stating 'architecture-free neural network library built around neuroevolution'.
matched fp:9be07272df3afc3f, llm:Topics: lstm, neat, neural-networks, neuro-evolution, recurrent-neural-networks, machine-learning, javascript; description: 'Evolutionary Neural Networks in JavaScript' and README stating 'architecture-free neural network library built around neuroevolution'.