Description
neurojs is a JavaScript framework for deep learning in the browser. It mainly focuses on reinforcement learning, but can be used for any neural network based task. It contains neat demos to visualise these capabilities, for instance a 2D self-driving car.
Feel free to contribute. The development on such projects is more awesome in a community!
neurojs alternatives and similar libraries
Based on the "Machine Learning" category.
Alternatively, view neurojs alternatives based on common mentions on social networks and blogs.
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Tesseract.js
Pure Javascript OCR for more than 100 Languages ๐๐๐ฅ -
ConvNetJS
Deep Learning in Javascript. Train Convolutional Neural Networks (or ordinary ones) in your browser. -
deeplearn.js
A hardware-accelerated machine intelligence library for the web. -
Brain.js
[UNMAINTAINED] Simple feed-forward neural network in JavaScript -
Synaptic.js
architecture-free neural network library for node.js and the browser -
m2cgen
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies -
Synapses
A group of neural-network libraries for functional and mainstream languages -
TensorFlow.js
A JavaScript library for training and deploying ML models in the browser and on Node.js.
Appwrite - The Open Source Firebase alternative introduces iOS support
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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README
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neurojs is a JavaScript framework for deep learning in the browser. It mainly focuses on reinforcement learning, but can be used for any neural network based task. It contains neat demos to visualise these capabilities, for instance a 2D self-driving car.
Feel free to contribute. The development on such projects is more awesome in a community!
Note: this repo is no longer maintained since more general frameworks such as TensorFlow-JS emerged, which I recommend you to use.
Features
- Implements a full-stack neural-network based machine learning framework
- Extended reinforcement-learning support
- Uniform and prioritised replay buffers
- Advantage-learning (increasing the action-gap) https://arxiv.org/pdf/1512.04860v1.pdf
- Support for deep-q-networks and actor-critic models (via deep-deterministic-policy-gradients)
- Binary import and export of network configurations (weights etc.)
- High-performance
Examples
- Self-driving car
- Advanced XOR
- Andrej Karpathy's Waterworld (ConvNetJS replaced with NeuroJS)
Running the examples
npm install
npm start
Open http://localhost:8080/examples/
in your browser and select the demo you want to run.
What's next?
- More examples (pong, pendulum, snake,improved cars, etc.)
- Support for web workers
- LSTM and backpropagation through time