Javascript

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Top Javascript Machine Learning libraries in 2019 | Jason Shin - Towards Data Science - Medium
11 Javascript Machine Learning Libraries for 2019 | Jonathan Saring - Bits and Pieces - Medium
A Web Developer's Guide to Machine Learning in JavaScript | Robin Wieruch
Neural networks in JavaScript - Brain.js | Robert Plummer
Machine Learning in Node.js With TensorFlow.js | James Thomas
Visualization
NPM JavaScript package registry
- Yarn package manager for JavaScript

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- Keras.js No longer active - capability now is in TensorFlow.js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