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(A sampling of available Javascript Machine Learning libraries)
(A sampling of available Javascript Machine Learning libraries)
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* [http://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle&regDataset=reg-plane&learningRate=0.03&regularizationRate=0&noise=0&networkShape=4,2&seed=0.08014&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false Tensorflow Deep Playground]; written in [http://www.typescriptlang.org/ TypeScript] using [http://d3js.org/ d3.js]
 
* [http://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle&regDataset=reg-plane&learningRate=0.03&regularizationRate=0&noise=0&networkShape=4,2&seed=0.08014&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false Tensorflow Deep Playground]; written in [http://www.typescriptlang.org/ TypeScript] using [http://d3js.org/ d3.js]
 
* [http://github.com/BrainJS/brain.js brain.js] in browser and [http://nodejs.org/en/ Node.js] ..see [http://scrimba.com/g/gneuralnetworks introduction]  
 
* [http://github.com/BrainJS/brain.js brain.js] in browser and [http://nodejs.org/en/ Node.js] ..see [http://scrimba.com/g/gneuralnetworks introduction]  
* [http://github.com/NaturalNode/natural Natural] provides tokenizing, stemming (reducing a word to a not-necessarily morphological root), classification, phonetics, tf-idf, WordNet, string similarity, some inflections, and more. (nodejs)
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* [http://github.com/NaturalNode/natural Natural] provides tokenizing, stemming (reducing a word to a not-necessarily morphological root), classification, phonetics, [[Term Frequency–Inverse Document Frequency (TF-IDF)]], [http://wordnet.princeton.edu/ WordNet], string similarity, some inflections, and more. (nodejs)
 
* [http://github.com/NeuroJS Neuro.js] [http://janhuenermann.com/projects/learning-to-drive Learning to Drive project] a deep learning and reinforcement learning Javascript library framework for the browser. Implementing a full stack neural-network based machine learning framework with extended reinforcement-learning support
 
* [http://github.com/NeuroJS Neuro.js] [http://janhuenermann.com/projects/learning-to-drive Learning to Drive project] a deep learning and reinforcement learning Javascript library framework for the browser. Implementing a full stack neural-network based machine learning framework with extended reinforcement-learning support
* [http://tenso.rs/ TensorFire] is a framework for running neural networks in the browser, accelerated by WebGL
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* [http://tenso.rs/ TensorFire] is a framework for running neural networks in the browser, accelerated by [http://get.webgl.org/ WebGL]
 
* [http://github.com/karpathy/convnetjs Conventjs] (not maintained)] neural networks supporting common modules, classification, [[Regression]], an experimental Reinforcement Learning module, able to train convolutional networks that process images
 
* [http://github.com/karpathy/convnetjs Conventjs] (not maintained)] neural networks supporting common modules, classification, [[Regression]], an experimental Reinforcement Learning module, able to train convolutional networks that process images
 
* [[ConvNetJS]] an NPM version is also available for those using [http://nodejs.org/en/ Node.js], and the library is designed to make proper use of Javascript’s asynchronicity.
 
* [[ConvNetJS]] an NPM version is also available for those using [http://nodejs.org/en/ Node.js], and the library is designed to make proper use of Javascript’s asynchronicity.
 
* [http://github.com/mljs/ml mljs] includes supervised and unsupervised learning, artificial neural networks, [[Regression]] algorithms and supporting libraries for statistics, math etc.
 
* [http://github.com/mljs/ml mljs] includes supervised and unsupervised learning, artificial neural networks, [[Regression]] algorithms and supporting libraries for statistics, math etc.
 
* [http://github.com/cazala/synaptic Synaptic] multilayer perceptrons, multilayer long-short term memory networks, liquid state machines and a trainer capable of training a verity of networks
 
* [http://github.com/cazala/synaptic Synaptic] multilayer perceptrons, multilayer long-short term memory networks, liquid state machines and a trainer capable of training a verity of networks
* [http://mil-tokyo.github.io/webdnn/ Webdnn] this framework optimizes the DNN model to compress the model data and accelerate execution through Javascript APIs such as WebAssembly and WebGPU   
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* [http://mil-tokyo.github.io/webdnn/ Webdnn] this framework optimizes the [[Deep Neural Network (DNN)]] model to compress the model data and accelerate execution through Javascript APIs such as [http://webassembly.org/ WebAssembly] and [http://gpuweb.github.io/gpuweb/ WebGPU]  
* [http://wagenaartje.github.io/neataptic/ Neataptic] neuro-evolution & backpropagation for the browser
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* [http://wagenaartje.github.io/neataptic/ Neataptic] neuro-evolution & [[backpropagation]] for the browser
 
* [http://stevenmiller888.github.io/mindjs.net/ Mind] make predictions, using a matrix implementation to process training data and enabling configurable network topology.
 
* [http://stevenmiller888.github.io/mindjs.net/ Mind] make predictions, using a matrix implementation to process training data and enabling configurable network topology.
 
* [http://deepforge.readthedocs.io/en/latest/deployment/overview.html DeeForge] a development environment for deep learning
 
* [http://deepforge.readthedocs.io/en/latest/deployment/overview.html DeeForge] a development environment for deep learning

Revision as of 09:11, 29 March 2020

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A sampling of available Javascript Machine Learning libraries

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Demos

Node.js

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