Difference between revisions of "JavaScript"
(→A sampling of available Javascript Machine Learning libraries) |
(→A sampling of available Javascript Machine Learning libraries) |
||
| Line 25: | Line 25: | ||
* [http://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle®Dataset=reg-plane&learningRate=0.03®ularizationRate=0&noise=0&networkShape=4,2&seed=0.08014&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false Tensorflow Deep Playground]; written in [http://www.typescriptlang.org/ TypeScript] using [http://d3js.org/ d3.js] | * [http://playground.tensorflow.org/#activation=tanh&batchSize=10&dataset=circle®Dataset=reg-plane&learningRate=0.03®ularizationRate=0&noise=0&networkShape=4,2&seed=0.08014&showTestData=false&discretize=false&percTrainData=50&x=true&y=true&xTimesY=false&xSquared=false&ySquared=false&cosX=false&sinX=false&cosY=false&sinY=false&collectStats=false&problem=classification&initZero=false&hideText=false Tensorflow Deep Playground]; written in [http://www.typescriptlang.org/ TypeScript] using [http://d3js.org/ d3.js] | ||
* [http://github.com/BrainJS/brain.js brain.js] in browser and [http://nodejs.org/en/ Node.js] ..see [http://scrimba.com/g/gneuralnetworks introduction] | * [http://github.com/BrainJS/brain.js brain.js] in browser and [http://nodejs.org/en/ Node.js] ..see [http://scrimba.com/g/gneuralnetworks introduction] | ||
| − | * [http://github.com/NaturalNode/natural Natural] provides tokenizing, stemming (reducing a word to a not-necessarily morphological root), classification, phonetics, | + | * [http://github.com/NaturalNode/natural Natural] provides tokenizing, stemming (reducing a word to a not-necessarily morphological root), classification, phonetics, [[Term Frequency–Inverse Document Frequency (TF-IDF)]], [http://wordnet.princeton.edu/ WordNet], string similarity, some inflections, and more. (nodejs) |
* [http://github.com/NeuroJS Neuro.js] [http://janhuenermann.com/projects/learning-to-drive 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 | * [http://github.com/NeuroJS Neuro.js] [http://janhuenermann.com/projects/learning-to-drive 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 | ||
| − | * [http://tenso.rs/ TensorFire] is a framework for running neural networks in the browser, accelerated by WebGL | + | * [http://tenso.rs/ TensorFire] is a framework for running neural networks in the browser, accelerated by [http://get.webgl.org/ WebGL] |
* [http://github.com/karpathy/convnetjs Conventjs] (not maintained)] neural networks supporting common modules, classification, [[Regression]], an experimental Reinforcement Learning module, able to train convolutional networks that process images | * [http://github.com/karpathy/convnetjs 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 [http://nodejs.org/en/ Node.js], and the library is designed to make proper use of Javascript’s asynchronicity. | * [[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. | ||
* [http://github.com/mljs/ml mljs] includes supervised and unsupervised learning, artificial neural networks, [[Regression]] algorithms and supporting libraries for statistics, math etc. | * [http://github.com/mljs/ml mljs] includes supervised and unsupervised learning, artificial neural networks, [[Regression]] algorithms and supporting libraries for 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 DNN model to compress the model data and accelerate execution through Javascript APIs such as WebAssembly and 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] |
| − | * [http://wagenaartje.github.io/neataptic/ Neataptic] neuro-evolution & backpropagation for the browser | + | * [http://wagenaartje.github.io/neataptic/ Neataptic] neuro-evolution & [[backpropagation]] for the browser |
* [http://stevenmiller888.github.io/mindjs.net/ Mind] make predictions, using a matrix implementation to process training data and enabling configurable network topology. | * [http://stevenmiller888.github.io/mindjs.net/ Mind] make predictions, using a matrix implementation to process training data and enabling configurable network topology. | ||
* [http://deepforge.readthedocs.io/en/latest/deployment/overview.html DeeForge] a development environment for deep learning | * [http://deepforge.readthedocs.io/en/latest/deployment/overview.html DeeForge] a development environment for deep learning | ||
Revision as of 09:11, 29 March 2020
Youtube search... ...Google search
- 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
- 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
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 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, 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
- 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 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 with Python and underlying Javascript libraries
- 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
- 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
________________________________
Demos
Node.js
Youtube search... ...Google search
- Node.js
- Watch me Build a Marketing Startup | Siraj Raval
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