Difference between revisions of "JavaScript"

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* [http://blog.bitsrc.io/10-javascript-iot-libraries-to-use-in-your-next-projects-bef5f9136f83 10 Javascript IoT Libraries To Use In Your Next Project |] [http://blog.bitsrc.io/@JonathanSaring Jonathan Saring]
 
* [http://blog.bitsrc.io/10-javascript-iot-libraries-to-use-in-your-next-projects-bef5f9136f83 10 Javascript IoT Libraries To Use In Your Next Project |] [http://blog.bitsrc.io/@JonathanSaring Jonathan Saring]
 
* [http://scrimba.com/g/gneuralnetworks Neural networks in JavaScript - Brain.js | Robert Plummer]
 
* [http://scrimba.com/g/gneuralnetworks Neural networks in JavaScript - Brain.js | Robert Plummer]
* [http://www.kdnuggets.com/2019/01/five-best-data-visualization-libraries.html The Five Best Data Visualization Libraries | Lio Fleishman, Sisense]
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* [[Visualization]]
  
 
* 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:

Revision as of 16:59, 19 January 2019

Youtube search... ...Google search

  • 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 runs Keras models in the browser, with GPU support using WebGL. since Keras uses a number of frameworks as backends, the models can be trained in TensorFlow, CNTK, and other frameworks as well.
    • 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
    • Conventjs (not maintained)] neural networks supporting common modules, classification, regression, an experimental Reinforcement Learning module, able to train convolutional networks that process images
    • 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
    • brain.js several types of networks
    • 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
    • Compromise modest natural-language processing (NLP) interprets and pre-parses English and makes some reasonable decisions
    • Mind make predictions, using a matrix implementation to process training data and enabling configurable network topology.
    • Natural provides tokenizing, stemming (reducing a word to a not-necessarily morphological root), classification, phonetics, tf-idf, WordNet, string similarity, and more.
    • DeeForge a development environment for deep learning

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Node.js

Youtube search...

Demos