](https://nni.readthedocs.io/en/stable)
NNI automates feature engineering, neural architecture search, hyperparameter tuning, and model compression for deep learning. Find the latest features, API, examples and tutorials in our **[official documentation](https://nni.readthedocs.io/) ([简体中文版点这里](https://nni.readthedocs.io/zh/stable))**.
## What's NEW! 
* **New release**: [v3.0 preview is available](https://github.com/microsoft/nni/releases/tag/v3.0rc1) - _released on May-5-2022_
* **New demo available**: [Youtube entry](https://www.youtube.com/channel/UCKcafm6861B2mnYhPbZHavw) | [Bilibili 入口](https://space.bilibili.com/1649051673) - _last updated on June-22-2022_
* **New research paper**: [SparTA: Deep-Learning Model Sparsity via Tensor-with-Sparsity-Attribute](https://www.usenix.org/system/files/osdi22-zheng-ningxin.pdf) - _published in OSDI 2022_
* **New research paper**: [Privacy-preserving Online AutoML for Domain-Specific Face Detection](https://openaccess.thecvf.com/content/CVPR2022/papers/Yan_Privacy-Preserving_Online_AutoML_for_Domain-Specific_Face_Detection_CVPR_2022_paper.pdf) - _published in CVPR 2022_
* **Newly upgraded documentation**: [Doc upgraded](https://nni.readthedocs.io/en/stable)
## Installation
See the [NNI installation guide](https://nni.readthedocs.io/en/stable/installation.html) to install from pip, or build from source.
To install the current release:
```
$ pip install nni
```
To update NNI to the latest version, add `--upgrade` flag to the above commands.
## NNI capabilities in a glance
Hyperparameter Tuning
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Neural Architecture Search
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Model Compression
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Supported Frameworks
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Training Services
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Tutorials
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| Supports |
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## Resources
* [NNI Documentation Homepage](https://nni.readthedocs.io/en/stable)
* [NNI Installation Guide](https://nni.readthedocs.io/en/stable/installation.html)
* [NNI Examples](https://nni.readthedocs.io/en/latest/examples.html)
* [Python API Reference](https://nni.readthedocs.io/en/latest/reference/python_api.html)
* [Releases (Change Log)](https://nni.readthedocs.io/en/latest/release.html)
* [Related Research and Publications](https://nni.readthedocs.io/en/latest/notes/research_publications.html)
* [Youtube Channel of NNI](https://www.youtube.com/channel/UCKcafm6861B2mnYhPbZHavw)
* [Bilibili Space of NNI](https://space.bilibili.com/1649051673)
* [Webinar of Introducing Retiarii: A deep learning exploratory-training framework on NNI](https://note.microsoft.com/MSR-Webinar-Retiarii-Registration-Live.html)
* [Community Discussions](https://github.com/microsoft/nni/discussions)
## Contribution guidelines
If you want to contribute to NNI, be sure to review the [contribution guidelines](https://nni.readthedocs.io/en/stable/notes/contributing.html), which includes instructions of submitting feedbacks, best coding practices, and code of conduct.
We use [GitHub issues](https://github.com/microsoft/nni/issues) to track tracking requests and bugs.
Please use [NNI Discussion](https://github.com/microsoft/nni/discussions) for general questions and new ideas.
For questions of specific use cases, please go to [Stack Overflow](https://stackoverflow.com/questions/tagged/nni).
Participating discussions via the following IM groups is also welcomed.
|Gitter||WeChat|
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Over the past few years, NNI has received thousands of feedbacks on GitHub issues, and pull requests from hundreds of contributors.
We appreciate all contributions from community to make NNI thrive.
