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[docs] Why Tune? (#8790)

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Co-authored-by: Sumanth Ratna <sumanthratna@gmail.com>
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Richard Liaw
2020-06-11 11:23:36 -07:00
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co-authored by Sumanth Ratna
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doc/source/tune/_tutorials/overview.rst
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@@ -176,3 +176,15 @@ Contributed Examples
- `pbt_tune_cifar10_with_keras <https://github.com/ray-project/ray/blob/master/python/ray/tune/examples/pbt_tune_cifar10_with_keras.py>`__: A contributed example of tuning a Keras model on CIFAR10 with the PopulationBasedTraining scheduler.
- `genetic_example <https://github.com/ray-project/ray/blob/master/python/ray/tune/examples/genetic_example.py>`__: Optimizing the michalewicz function using the contributed GeneticSearch algorithm with AsyncHyperBandScheduler.
- `tune_cifar10_gluon <https://github.com/ray-project/ray/blob/master/python/ray/tune/examples/tune_cifar10_gluon.py>`__: MXNet Gluon example to use Tune with the function-based API on CIFAR-10 dataset.
Open Source Projects using Tune
-------------------------------
Here are some of the popular open source repositories and research projects that leverage Tune. Feel free to submit a pull-request adding (or requesting a removal!) of a listed project.
- `Softlearning <https://github.com/rail-berkeley/softlearning>`_: Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
- `Flambe <https://github.com/asappresearch/flambe>`_: An ML framework to accelerate research and its path to production. See `flambe.ai <https://flambe.ai>`_.
- `Population Based Augmentation <https://github.com/arcelien/pba>`_: Population Based Augmentation (PBA) is a algorithm that quickly and efficiently learns data augmentation functions for neural network training. PBA matches state-of-the-art results on CIFAR with one thousand times less compute.
- `Fast AutoAugment by Kakao <https://github.com/kakaobrain/fast-autoaugment>`_: Fast AutoAugment (Accepted at NeurIPS 2019) learns augmentation policies using a more efficient search strategy based on density matching.
- `Allentune <https://github.com/allenai/allentune>`_: Hyperparameter Search for AllenNLP from AllenAI.
- `machinable <https://github.com/frthjf/machinable>`_: A modular configuration system for machine learning research. See `machinable.org <https://machinable.org>`_.