Javascript

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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)
    • Keras.js No longer active - capability now is in TensorFlow.js
    • Deeplearnjs rebranded to TensorFlow.js
  • 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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Demos

Node.js

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React

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