JavaScript

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  • Natural Language Tools & Services
  • 10 Javascript IoT Libraries To Use In Your Next Project | Jonathan Saring
  • Neural networks in JavaScript - Brain.js | Robert Plummer
  • Visualization
  • Natural Language Processing and Machine Learning in JavaScript | David Luecke - Medium
  • A sampling of available Javascript Machine Learning libraries:
    • TensorFlow.js for training and deploying ML models in the browser and on Node.js (was called Deeplearnjs)
    • Keras.js runs Keras models in the browser, with GPU support using WebGL. since Keras uses a number of frameworks as backends, the models can be trained in TensorFlow, CNTK, and other frameworks as well.
    • brain.js several types of networks
    • 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.
    • 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
    • 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.

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Node.js

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Demos