Difference between revisions of "JavaScript"
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* [http://github.com/dmlc/mxnet.js/ 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 | * [http://github.com/dmlc/mxnet.js/ 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 | ||
| − | ==== [http://neo4j.com/use-cases/artificial-intelligence-analytics/ Graphs Are Fundamental to Modern AI Systems | neo4j] | + | ==== Graphics ==== |
| + | * [http://neo4j.com/use-cases/artificial-intelligence-analytics/ Graphs Are Fundamental to Modern AI Systems | neo4j] | ||
* [http://www.datanami.com/2018/03/20/why-knowledge-graphs-are-foundational-to-artificial-intelligence/ Why Knowledge Graphs Are Foundational to Artificial Intelligence | Jim Webber] | * [http://www.datanami.com/2018/03/20/why-knowledge-graphs-are-foundational-to-artificial-intelligence/ Why Knowledge Graphs Are Foundational to Artificial Intelligence | Jim Webber] | ||
* [http://www.cbronline.com/opinion/creating-sophisticated-recommendations-native-graphs Creating The Most Sophisticated Recommendations Using Native Graphs | Emil Eifrem] | * [http://www.cbronline.com/opinion/creating-sophisticated-recommendations-native-graphs Creating The Most Sophisticated Recommendations Using Native Graphs | Emil Eifrem] | ||
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* [http://d3js.org/ D3js.org] - [http://bl.ocks.org/heybignick/3faf257bbbbc7743bb72310d03b86ee8 D3.js v4 Force Directed Graph with Labels] | * [http://d3js.org/ D3js.org] - [http://bl.ocks.org/heybignick/3faf257bbbbc7743bb72310d03b86ee8 D3.js v4 Force Directed Graph with Labels] | ||
** [http://playground.tensorflow.org TensorFlow Deep Playground] an interactive visualization of neural networks, written in TypeScript using d3.js and can be repurposed for different means | ** [http://playground.tensorflow.org TensorFlow Deep Playground] an interactive visualization of neural networks, written in TypeScript using d3.js and can be repurposed for different means | ||
| + | * [http://get.webgl.org/ 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. | ||
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* [[Git - GitHub and GitLab]] | * [[Git - GitHub and GitLab]] | ||
Revision as of 05:32, 25 July 2019
Youtube search... ...Google search
- 11 Javascript Machine Learning Libraries for 2019 | Jonathan Saring - Bits and Pieces Medium
- 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
- Machine Learning in Node.js With TensorFlow.js | James Thomas
- 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
- 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
Graphics
- 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
- 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.
________________________________
Node.js
- Watch me Build a Marketing Startup | Siraj Raval