Difference between revisions of "JavaScript"
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==== A [http://news.ycombinator.com/item?id=16718285 sampling] of [http://blog.bitsrc.io/11-javascript-machine-learning-libraries-to-use-in-your-app-c49772cca46c available] Javascript Machine Learning libraries ==== | ==== A [http://news.ycombinator.com/item?id=16718285 sampling] of [http://blog.bitsrc.io/11-javascript-machine-learning-libraries-to-use-in-your-app-c49772cca46c available] Javascript Machine Learning libraries ==== | ||
* Libraries for NLP see [[Natural Language Tools & Services]] | * 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) | + | *[[TensorFlow.js]] for training and deploying ML models in the browser and on [http://nodejs.org/en/ Node.js] (was called Deeplearnjs) |
** [http://transcranial.github.io/keras-js/#/ Keras.js] No longer active - capability now is in TensorFlow.js | ** [http://transcranial.github.io/keras-js/#/ Keras.js] No longer active - capability now is in TensorFlow.js | ||
** [http://deeplearnjs.org/ Deeplearnjs] rebranded to TensorFlow.js | ** [http://deeplearnjs.org/ Deeplearnjs] rebranded to TensorFlow.js | ||
| − | * [http://github.com/BrainJS/brain.js brain.js] in browser and | + | * [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/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 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 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 | ||
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<youtube>TjQmZeyIiTk</youtube> | <youtube>TjQmZeyIiTk</youtube> | ||
| − | === Node.js === | + | === [http://nodejs.org/en/ Node.js] === |
[http://www.youtube.com/results?search_query=node.js+artificial+intelligence+deep+learning Youtube search...] | [http://www.youtube.com/results?search_query=node.js+artificial+intelligence+deep+learning Youtube search...] | ||
Revision as of 19:59, 23 April 2019
Youtube search... ...Google search
- 10 Javascript IoT Libraries To Use In Your Next Project | Jonathan Saring
- A Web Developer's Guide to Machine Learning in JavaScript | Robin Wieruch
- Neural networks in JavaScript - Brain.js | Robert Plummer
- Visualization
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
- 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.
- 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
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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Node.js
