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From September 2018 to September 2019, We are still moving on …


 **Great news!**&nbsp;&nbsp;With the tag of **Scalability** and **Ease of Use**, NNI v1.0 is comming. Based on the various types of [Tuning Algorithms](./Tuner/BuiltinTuner.md), NNI has supported the Hyperparameter tuning, Neural Architecture search and Auto-Feature-Engineering, which is an exciting news for algorithmic engineers; besides these, NNI v1.0 has made many improvements in the optimization of tuning algorithm, [WebUI's simplicity and intuition](./Tutorial/WebUI.md) and [Platform diversification](./TrainingService/SupportTrainingService.md). NNI has grown into a more intelligent automated machine learning (AutoML) toolkit.
 


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&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;**Step one**: Start with the [Tutorial Doc](./Tutorial/Installation.md), and install NNI v1.0 first.<br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;**Step two**: Find a " Hello world example", follow the [Tutorial Doc](./Tutorial/QuickStart.md) and have a Quick Start. <br>
&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;**Step three**: Get familiar with the [WebUI Tutorial](./Tutorial/WebUI.md) and let NNI better assists with your tuning tour.<br>

The fully automated tool greatly improves the efficiency of the tuning process. For more detail about the 1.0 updates, you can refer to [Release 1.0](https://github.com/microsoft/nni/releases). More of our advance plan, you can refer to our [Roadmap](https://github.com/microsoft/nni/wiki/Roadmap). Besides, we also welcome more and more contributors to join us, there are many ways to participate, please refer to [How to contribute](./Tutorial/Contributing.md) for more details.