Software:Neural Network Intelligence
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Short description: Microsoft open source library
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| Original author(s) | Microsoft Research |
|---|---|
| Developer(s) | Microsoft |
| Initial release | 2018[1] |
| Stable release | v2.10[2]
/ November 14, 2022 |
| Repository | github |
| Written in | Python |
| Operating system | Windows, macOS, Ubuntu |
| Platform | Cross-platform |
| Type | AutoML toolkit |
| License | MIT License |
| Website | nni |
NNI (Neural Network Intelligence) is a free and open-source AutoML toolkit developed by Microsoft.[3][4] It is used to automate feature engineering, model compression, neural architecture search, and hyper-parameter tuning.[5][6]
The source code is licensed under MIT License and available on GitHub.[7]
See also
References
- ↑ "Tags · microsoft/nni · GitHub". 10 September 2021. https://github.com/microsoft/nni/releases/tag/v0.1.
- ↑ "Tags · microsoft/nni · GitHub". 28 June 2022. https://github.com/microsoft/nni/tags.
- ↑ Raschka, Sebastian; Patterson, Joshua; Nolet, Corey (April 11, 2020). "Machine Learning in Python: Main Developments and Technology Trends in Data Science, Machine Learning, and Artificial Intelligence". Information 11 (4): 193. doi:10.3390/info11040193.
- ↑ "Open Source AutoML Tools: AutoGluon, TransmogrifAI, Auto-sklearn, and NNI". June 16, 2020. http://www.bizety.com/2020/06/16/open-source-automl-tools-autogluon-transmogrifai-auto-sklearn-and-nni/.
- ↑ Heller, Martin (August 21, 2019). "Automated machine learning or AutoML explained". https://www.infoworld.com/article/3430788/automated-machine-learning-or-automl-explained.html.
- ↑ "15 Undiscovered & Open Source Machine Learning Frameworks You Need to Know in 2020.". June 4, 2020. https://www.freecodecamp.org/news/15-undiscovered-open-source-machine-learning-frameworks-you-need-to-know-in-2020/.
- ↑ "microsoft/nni". August 11, 2020. https://github.com/microsoft/nni.
Further reading
- Automated Deep Learning Using Neural Network Intelligence: Develop and Design PyTorch and TensorFlow Models Using Python. Apress. 2022. ISBN 978-1484281482.
External links
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