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.github/dependabot.yml vendored
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version: 2
updates:
- package-ecosystem: "github-actions"
directory: "/"
schedule:
interval: "daily"

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README.md
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@ -94,7 +94,7 @@ You can find a detailed documentation about FLAML [here](https://microsoft.githu
In addition, you can find: In addition, you can find:
- Demo and tutorials of FLAML [here](https://www.youtube.com/channel/UCfU0zfFXHXdAd5x-WvFBk5A). - [Talks](https://www.youtube.com/channel/UCfU0zfFXHXdAd5x-WvFBk5A) and [tutorials](https://github.com/microsoft/FLAML/tree/tutorial/tutorial) about FLAML.
- Research around FLAML [here](https://microsoft.github.io/FLAML/docs/Research). - Research around FLAML [here](https://microsoft.github.io/FLAML/docs/Research).

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website/docs/Getting-Started.md
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@ -90,7 +90,7 @@ Then, you can use it just like you use the original `LGMBClassifier`. Your other
* Understand the use cases for [Task-oriented AutoML](Use-Cases/task-oriented-automl), [Tune user-defined function](Use-Cases/Tune-User-Defined-Function) and [Zero-shot AutoML](Use-Cases/Zero-Shot-AutoML). * Understand the use cases for [Task-oriented AutoML](Use-Cases/task-oriented-automl), [Tune user-defined function](Use-Cases/Tune-User-Defined-Function) and [Zero-shot AutoML](Use-Cases/Zero-Shot-AutoML).
* Find code examples under "Examples": from [AutoML - Classification](Examples/AutoML-Classification) to [Tune - PyTorch](Examples/Tune-PyTorch). * Find code examples under "Examples": from [AutoML - Classification](Examples/AutoML-Classification) to [Tune - PyTorch](Examples/Tune-PyTorch).
* Watch [video tutorials](https://www.youtube.com/channel/UCfU0zfFXHXdAd5x-WvFBk5A). * Find [talks](https://www.youtube.com/channel/UCfU0zfFXHXdAd5x-WvFBk5A) and [tutorials](https://github.com/microsoft/FLAML/tree/tutorial/tutorial) about FLAML.
* Learn about [research](Research) around FLAML. * Learn about [research](Research) around FLAML.
* Refer to [SDK](reference/automl) and [FAQ](FAQ). * Refer to [SDK](reference/automl) and [FAQ](FAQ).