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**NNI (Neural Network Intelligence)** is a lightweight but powerful toolkit to help users **automate**<ahref="docs/en_US/FeatureEngineering/Overview.rst">Feature Engineering</a>, <ahref="docs/en_US/NAS/Overview.rst">Neural Architecture Search</a>, <ahref="docs/en_US/Tuner/BuiltinTuner.rst">Hyperparameter Tuning</a> and <ahref="docs/en_US/Compression/Overview.rst">Model Compression</a>.
**NNI (Neural Network Intelligence)** is a lightweight but powerful toolkit to help users **automate**<ahref="docs/en_US/FeatureEngineering/Overview.rst">Feature Engineering</a>, <ahref="docs/en_US/NAS/Overview.rst">Neural Architecture Search</a>, <ahref="docs/en_US/Tuner/BuiltinTuner.rst">Hyperparameter Tuning</a> and <ahref="docs/en_US/Compression/Overview.rst">Model Compression</a>.
The tool manages automated machine learning (AutoML) experiments, **dispatches and runs** experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in **different training environments** like <ahref="docs/en_US/TrainingService/LocalMode.rst">Local Machine</a>, <ahref="docs/en_US/TrainingService/RemoteMachineMode.rst">Remote Servers</a>, <ahref="docs/en_US/TrainingService/PaiMode.rst">OpenPAI</a>, <ahref="docs/en_US/TrainingService/KubeflowMode.rst">Kubeflow</a>, <ahref="docs/en_US/TrainingService/FrameworkControllerMode.rst">FrameworkController on K8S (AKS etc.)</a>, <ahref="docs/en_US/TrainingService/DLTSMode.rst">DLWorkspace (aka. DLTS)</a>, <ahref="docs/en_US/TrainingService/AMLMode.rst">AML (Azure Machine Learning)</a>, <ahref="docs/en_US/TrainingService/AdaptDLMode.rst">AdaptDL (aka. ADL)</a>and other cloud options.
The tool manages automated machine learning (AutoML) experiments, **dispatches and runs** experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in **different training environments** like <ahref="docs/en_US/TrainingService/LocalMode.rst">Local Machine</a>, <ahref="docs/en_US/TrainingService/RemoteMachineMode.rst">Remote Servers</a>, <ahref="docs/en_US/TrainingService/PaiMode.rst">OpenPAI</a>, <ahref="docs/en_US/TrainingService/KubeflowMode.rst">Kubeflow</a>, <ahref="docs/en_US/TrainingService/FrameworkControllerMode.rst">FrameworkController on K8S (AKS etc.)</a>, <ahref="docs/en_US/TrainingService/DLTSMode.rst">DLWorkspace (aka. DLTS)</a>, <ahref="docs/en_US/TrainingService/AMLMode.rst">AML (Azure Machine Learning)</a>, <ahref="docs/en_US/TrainingService/AdaptDLMode.rst">AdaptDL (aka. ADL)</a>, other cloud options and even <ahref="docs/en_US/TrainingService/HybridMode.rst">Hybrid mode</a>.
## **Who should consider using NNI**
## **Who should consider using NNI**
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* Researchers and data scientists who want to easily **implement and experiment new AutoML algorithms**, may it be: hyperparameter tuning algorithm, neural architect search algorithm or model compression algorithm.
* Researchers and data scientists who want to easily **implement and experiment new AutoML algorithms**, may it be: hyperparameter tuning algorithm, neural architect search algorithm or model compression algorithm.
* ML Platform owners who want to **support AutoML in their platform**.
* ML Platform owners who want to **support AutoML in their platform**.
### **[NNI v1.9 has been released!](https://github.com/microsoft/nni/releases) <a href="#nni-released-reminder"><img width="48" src="docs/img/release_icon.png"></a>**
### **[NNI v2.0 has been released!](https://github.com/microsoft/nni/releases) <a href="#nni-released-reminder"><img width="48" src="docs/img/release_icon.png"></a>**
## **NNI capabilities in a glance**
## **NNI capabilities in a glance**
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* To learn about what's NNI, read the [NNI Overview](https://nni.readthedocs.io/en/latest/Overview.html).
* To get yourself familiar with how to use NNI, read the [documentation](https://nni.readthedocs.io/en/latest/index.html).
* To get started and install NNI on your system, please refer to [Install NNI](https://nni.readthedocs.io/en/latest/installation.html).
## **Contributing**
## **Contributing**
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.
