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talks and tutorials (#694)
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@@ -94,7 +94,7 @@ You can find a detailed documentation about FLAML [here](https://microsoft.githu
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In addition, you can find:
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- Demo and tutorials of FLAML [here](https://www.youtube.com/channel/UCfU0zfFXHXdAd5x-WvFBk5A).
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- [Talks](https://www.youtube.com/channel/UCfU0zfFXHXdAd5x-WvFBk5A) and [tutorials](https://github.com/microsoft/FLAML/tree/tutorial/tutorial) about FLAML.
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- Research around FLAML [here](https://microsoft.github.io/FLAML/docs/Research).
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@@ -90,7 +90,7 @@ Then, you can use it just like you use the original `LGMBClassifier`. Your other
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* 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).
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* Find code examples under "Examples": from [AutoML - Classification](Examples/AutoML-Classification) to [Tune - PyTorch](Examples/Tune-PyTorch).
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* Watch [video tutorials](https://www.youtube.com/channel/UCfU0zfFXHXdAd5x-WvFBk5A).
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* Find [talks](https://www.youtube.com/channel/UCfU0zfFXHXdAd5x-WvFBk5A) and [tutorials](https://github.com/microsoft/FLAML/tree/tutorial/tutorial) about FLAML.
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* Learn about [research](Research) around FLAML.
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* Refer to [SDK](reference/automl) and [FAQ](FAQ).
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