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  • Keras.js No longer active - capability now is in TensorFlow.js
  • Deeplearnjs
• brain.js in browser and node.js ..see introduction
• 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.

• DeeForge a development environment for deep learning

Graphs Are Fundamental to Modern AI Systems | neo4j

• Why Knowledge Graphs Are Foundational to Artificial Intelligence | Jim Webber
• Creating The Most Sophisticated Recommendations Using Native Graphs | Emil Eifrem
• Neo4j Machine Learning Extensions
• Review prediction with Neo4j and TensorFlow | David Mack
• Knowledge Graphs
• D3js.org - D3.js v4 Force Directed Graph with Labels
  • TensorFlow Deep Playground an interactive visualization of neural networks, written in TypeScript using d3.js and can be repurposed for different means

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• Git - GitHub and GitLab
• Bit

Node.js

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Demos

• Land Lines
• Learning to Drive
• TensorFlow.js Demos