Difference between revisions of "JavaScript"
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* [http://tenso.rs/ TensorFire] is a framework for running neural networks in the browser, accelerated by [http://get.webgl.org/ WebGL] | * [http://tenso.rs/ TensorFire] is a framework for running neural networks in the browser, accelerated by [http://get.webgl.org/ WebGL] | ||
* [[ConvNetJS]] an NPM version is also available for those using [http://nodejs.org/en/ Node.js], and the library is designed to make proper use of Javascript’s asynchronicity with neural networks supporting common modules, classification, [[Regression]], an experimental Reinforcement Learning module, able to train [[(Deep) Convolutional Neural Network (DCNN/CNN)]] that process images | * [[ConvNetJS]] an NPM version is also available for those using [http://nodejs.org/en/ Node.js], and the library is designed to make proper use of Javascript’s asynchronicity with neural networks supporting common modules, classification, [[Regression]], an experimental Reinforcement Learning module, able to train [[(Deep) Convolutional Neural Network (DCNN/CNN)]] that process images | ||
| − | * [http://github.com/mljs/ml mljs] includes supervised and unsupervised learning, artificial neural networks, [[Regression]] algorithms and supporting libraries for [[ | + | * [http://github.com/mljs/ml mljs] includes supervised and unsupervised learning, artificial neural networks, [[Regression]] algorithms and supporting libraries for [[Math for Intelligence | statistics, math etc.]] |
* [http://github.com/cazala/synaptic Synaptic] multilayer perceptrons, multilayer long-short term memory networks, liquid state machines and a trainer capable of training a verity of networks | * [http://github.com/cazala/synaptic Synaptic] multilayer perceptrons, multilayer long-short term memory networks, liquid state machines and a trainer capable of training a verity of networks | ||
* [http://mil-tokyo.github.io/webdnn/ Webdnn] this framework optimizes the [[Deep Neural Network (DNN)]] model to compress the model data and accelerate execution through Javascript APIs such as [http://webassembly.org/ WebAssembly] and [http://gpuweb.github.io/gpuweb/ WebGPU] | * [http://mil-tokyo.github.io/webdnn/ Webdnn] this framework optimizes the [[Deep Neural Network (DNN)]] model to compress the model data and accelerate execution through Javascript APIs such as [http://webassembly.org/ WebAssembly] and [http://gpuweb.github.io/gpuweb/ WebGPU] | ||
Revision as of 09:46, 12 October 2020
Youtube search... ...Google search
- Python
- 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
- 10+ Javascript libraries to draw your own diagrams (2020 edition) | Hamza Ed-douibi - MOdeling LAnguages
- Machine Learning in Node.js With TensorFlow.js | James Thomas
- Visualization
- NPM Javascript package registry
- Yarn package manager for Javascript
- Learn Deno, a Node.js alternative | Beau Carnes - freeCodeCamp.org a Node.js alternative created by Ryan Dahl, the same person who created Node.js.
Contents
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 Playground written in Javascript (TypeScript) using D3.js
- Brain.js
- ML5.js
- Natural provides tokenizing, stemming (reducing a word to a not-necessarily morphological root), classification, phonetics, Term Frequency–Inverse Document Frequency (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
- 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 with neural networks supporting common modules, classification, Regression, an experimental Reinforcement Learning module, able to train (Deep) Convolutional Neural Network (DCNN/CNN) that process images
- 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 Deep Neural Network (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 / Visualization
- Visualization with Python and underlying Javascript libraries
- WebGL.js - (Web Graphics Library) is a Javascript API for rendering interactive 3D and 2D graphics within any compatible web browser without the use of plug-ins
- Knowledge Graphs
- 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
- D3.js - utilizes assets for HTML, CSS, and SVG integrating any visualization seamlessly into a web page, dashboard, or website
- 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
- D3 | Sisense
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Demos
Node.js
Youtube search... ...Google search
React
Youtube search... ...Google search
- React A Javascript library for building user interfaces
- Deep Learning With React Native | GeekyAnts - Medium
- Next.js the most popular component within React
