Difference between revisions of "JavaScript"
| Line 13: | Line 13: | ||
* [[Visualization]] | * [[Visualization]] | ||
* [http://medium.com/@daffl/natural-language-processing-and-machine-learning-in-javascript-249181a3b721 Natural Language Processing and Machine Learning in JavaScript | David Luecke - Medium] | * [http://medium.com/@daffl/natural-language-processing-and-machine-learning-in-javascript-249181a3b721 Natural Language Processing and Machine Learning in JavaScript | David Luecke - Medium] | ||
| − | + | ==== 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 ==== | |
| − | + | *[[TensorFlow.js]] for training and deploying ML models in the browser and on Node.js (was called Deeplearnjs) | |
| − | ** [http://transcranial.github.io/keras-js/#/ Keras.js] | + | ** [http://transcranial.github.io/keras-js/#/ Keras.js] No longer active - capability now is in TensorFlow.js |
| − | + | * [http://github.com/BrainJS/brain.js brain.js] several types of networks | |
| − | + | * [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://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. | |
| − | + | * [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/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://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://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://deepforge.readthedocs.io/en/latest/deployment/overview.html DeeForge] a development environment for deep learning | |
| − | + | ==== [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.cbronline.com/opinion/creating-sophisticated-recommendations-native-graphs Creating The Most Sophisticated Recommendations Using Native Graphs | Emil Eifrem] | |
| − | + | * [http://github.com/neo4j-contrib/neo4j-ml-procedures Neo4j Machine Learning Extensions] | |
| − | + | * [http://medium.com/octavian-ai/review-prediction-with-neo4j-and-tensorflow-1cd33996632a Review prediction with Neo4j and TensorFlow | David Mack] | |
| − | + | * [[Knowledge Graphs]] | |
| − | + | * [http://d3js.org/ D3js.org] - [http://bl.ocks.org/heybignick/3faf257bbbbc7743bb72310d03b86ee8 D3.js v4 Force Directed Graph with Labels] | |
________________________________ | ________________________________ | ||
Revision as of 07:03, 7 April 2019
Youtube search... ...Google search
- Natural Language Tools & Services
- 10 Javascript IoT Libraries To Use In Your Next Project | Jonathan Saring
- Neural networks in JavaScript - Brain.js | Robert Plummer
- Visualization
- Natural Language Processing and Machine Learning in JavaScript | David Luecke - Medium
Contents
A sampling of available Javascript Machine Learning libraries
- 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
- brain.js several types of networks
- 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.
- 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
- 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
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
________________________________
Node.js
