Difference between revisions of "JavaScript"

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(→‎A sampling of available Javascript Machine Learning libraries)
(→‎A sampling of available Javascript Machine Learning libraries)
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*[[TensorFlow.js]] for training and deploying ML models in the browser and on [http://nodejs.org/en/ Node.js] (was called Deeplearnjs)  
 
*[[TensorFlow.js]] for training and deploying ML models in the browser and on [http://nodejs.org/en/ Node.js] (was called Deeplearnjs)  
 
** [http://transcranial.github.io/keras-js/#/ Keras.js] No longer active - capability now is in [[TensorFlow.js]]
 
** [http://transcranial.github.io/keras-js/#/ Keras.js] No longer active - capability now is in [[TensorFlow.js]]
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** [http://deeplearnjs.org/ Deeplearnjs] rebranded to TensorFlow.js
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** [http://deeplearnjs.org/ Deeplearnjs] rebranded to [[TensorFlow.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://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]  

Revision as of 09:03, 29 March 2020

Youtube search... ...Google search

A sampling of available Javascript Machine Learning libraries

  • Libraries for NLP see Natural Language Tools & Services
  • TensorFlow.js for training and deploying ML models in the browser and on Node.js (was called Deeplearnjs)
  • Tensorflow Deep Playground; written in TypeScript using d3.js
  • brain.js in browser and Node.js ..see introduction
  • 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)
  • Neuro.js 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
  • TensorFire is a framework for running neural networks in the browser, accelerated by WebGL
  • 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 Node.js, and the library is designed to make proper use of Javascript’s asynchronicity.
  • mljs includes supervised and unsupervised learning, artificial neural networks, Regression algorithms and supporting libraries for statistics, math etc.
  • Synaptic multilayer perceptrons, multilayer long-short term memory networks, liquid state machines and a trainer capable of training a verity of networks
  • Webdnn this framework optimizes the DNN model to compress the model data and accelerate execution through Javascript APIs such as WebAssembly and WebGPU
  • Neataptic neuro-evolution & backpropagation for the browser
  • Mind make predictions, using a matrix implementation to process training data and enabling configurable network topology.
  • DeeForge a development environment for deep learning
  • MXnet.js deep learning in browser (without server); allows you to mix symbolic and imperative programming on the fly with a graph optimization layer for performance
  • Handtrack.js: Hand Tracking Interactions in the Browser using Tensorflow.js and 3 lines of code | Victor Dibia - Towards Data Science - allows you track a user’s hand (bounding box) from an image in any orientation

Graphics

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1*W79wtpbE2NTqUuFA8EVorQ.png

Demos

Node.js

Youtube search... ...Google search

React

Youtube search... ...Google search

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