Comparison_of_deep_learning_software

Comparison of deep learning software

Comparison of deep learning software

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The following table compares notable software frameworks, libraries and computer programs for deep learning.

Deep-learning software by name

More information Software, Creator ...
  1. Licenses here are a summary, and are not taken to be complete statements of the licenses. Some libraries may use other libraries internally under different licenses

Comparison of compatibility of machine learning models

[further explanation needed]

More information Format name, Design goal ...

See also


References

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  2. Atilim Gunes Baydin; Barak A. Pearlmutter; Alexey Andreyevich Radul; Jeffrey Mark Siskind (20 February 2015). "Automatic differentiation in machine learning: a survey". arXiv:1502.05767 [cs.LG].
  3. "Microsoft/caffe". GitHub. 30 October 2021.
  4. "Caffe | Model Zoo". caffe.berkeleyvision.org.
  5. GitHub - BVLC/caffe: Caffe: a fast open framework for deep learning., Berkeley Vision and Learning Center, 2019-09-25, retrieved 2019-09-25
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  9. Deeplearning4j. "Deeplearning4j on Spark". Deeplearning4j. Archived from the original on 2017-07-13. Retrieved 2016-09-01.{{cite web}}: CS1 maint: numeric names: authors list (link)
  10. "Metalhead". FluxML. 29 October 2021.
  11. "Intel® Math Kernel Library (Intel® MKL)". software.intel.com. September 11, 2018.
  12. "Deep Neural Network Functions". software.intel.com. May 24, 2019.
  13. "Using Intel® MKL with Threaded Applications". software.intel.com. June 1, 2017.
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  15. "Automatic Differentiation Background - MATLAB & Simulink". MathWorks. September 3, 2019. Retrieved November 19, 2019.
  16. "Neural Network Toolbox - MATLAB". MathWorks. Retrieved 13 November 2017.
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  19. "Restricted Boltzmann Machine with CNTK #534". GitHub, Inc. 27 May 2016. Retrieved 30 October 2023.
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  22. "MXNet Smart Device". ReadTheDocs. Archived from the original on 2016-09-21. Retrieved 2016-05-19.
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  24. "— Redirecting to mxnet.io". mxnet.readthedocs.io.
  25. "Model Gallery". GitHub. 29 October 2022.
  26. "PyTorch". Dec 17, 2021.
  27. Allaire, J.J.; Kalinowski, T.; Falbel, D.; Eddelbuettel, D.; Yuan, T.; Golding, N. (28 September 2023). "tensorflow: R Interface to 'TensorFlow'". The Comprehensive R Archive Network. Retrieved 30 October 2023.
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  32. "cltorch". GitHub.
  33. "Deep Learning — ROCm 4.5.0 documentation". Archived from the original on 2022-12-05. Retrieved 2022-09-27.

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