Difference between revisions of "Libraries & Frameworks"
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* [[PyTorch]] | * [[PyTorch]] | ||
* [[neon]] | * [[neon]] | ||
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* [[Deeplearning4j]] | * [[Deeplearning4j]] | ||
* [[theano]] | * [[theano]] | ||
* [[Scikit-learn]] | * [[Scikit-learn]] | ||
* [http://opencv.org/ OpenCV (Open Source Computer Vision Library)] | * [http://opencv.org/ OpenCV (Open Source Computer Vision Library)] | ||
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* [http://en.wikipedia.org/wiki/OpenCog OpenCog], a GPL-licensed framework for artificial intelligence written in C++, Python and Scheme. | * [http://en.wikipedia.org/wiki/OpenCog OpenCog], a GPL-licensed framework for artificial intelligence written in C++, Python and Scheme. | ||
* [http://en.wikipedia.org/wiki/RapidMiner RapidMiner], an environment for machine learning and [[data mining]], now developed commercially. | * [http://en.wikipedia.org/wiki/RapidMiner RapidMiner], an environment for machine learning and [[data mining]], now developed commercially. | ||
Revision as of 15:14, 15 July 2018
With pages at Primo.ai or not included in Wikipedia Deep learning comparison chart below
- Caffe / Caffe2
- Cognitive Toolkit (CNTK)
- gluon
- H20
- MXNet
- Neuroph
- PyTorch
- neon
- Deeplearning4j
- theano
- Scikit-learn
- OpenCV (Open Source Computer Vision Library)
- OpenCog, a GPL-licensed framework for artificial intelligence written in C++, Python and Scheme.
- RapidMiner, an environment for machine learning and data mining, now developed commercially.
- Weka, a free implementation of many machine learning algorithms in Java.