Difference between revisions of "JavaScript"
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[http://www.youtube.com/results?search_query=javascript+artificial+intelligence+deep+learning Youtube search...] | [http://www.youtube.com/results?search_query=javascript+artificial+intelligence+deep+learning Youtube search...] | ||
| − | *[[TensorFlow.js]] | + | *[[TensorFlow.js]] for training and deploying ML models in the browser and on Node.js (was called Deeplearnjs) |
| − | *[http://playground.tensorflow.org TensorFlow Playground written in Javascript] | + | *[http://playground.tensorflow.org TensorFlow Playground written in Javascript] (TypeScript) using d3.js |
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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: | ||
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* [http://github.com/mljs/ml mljs] | * [http://github.com/mljs/ml mljs] | ||
* [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://wagenaartje.github.io/neataptic/ Neataptic] neuro-evolution & backpropagation for the browser | * [http://wagenaartje.github.io/neataptic/ Neataptic] neuro-evolution & backpropagation for the browser | ||
| + | * [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://compromise.cool/ Compromise] modest natural-language processing (NLP) interprets and pre-parses English and makes some reasonable decisions | ||
| + | * [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 | ||
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Revision as of 09:29, 5 August 2018
- TensorFlow.js for training and deploying ML models in the browser and on Node.js (was called Deeplearnjs)
- TensorFlow Playground written in Javascript (TypeScript) using d3.js
A sampling of available Javascript Machine Learning libraries:
- mxnet.js
- webdnn
- brain.js several types of networks
- mljs
- 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
- Conventjs (not maintained)] neural networks supporting common modules, classification, regression, an experimental Reinforcement Learning module, able to train convolutional networks that process images
- Compromise modest natural-language processing (NLP) interprets and pre-parses English and makes some reasonable decisions
- 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
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Node.js
