* feat: update doc for pytorch estimator backend. * fix: remove ray global dependency. * rm: remove .swp file. * fix: revert ray import fix. * fix: replace model and optimizer with model_creator and optimizer_creator. * fix: delete unnecessary links. * fix: update index.md * fix: fix code style of quickstart and jupyter notebook. * fix: remove criterion. * fix: fix dataset description. * fix: fix code style. * fix: fix code style. * fix: update batch size and link * fix: update link * fix: fix code style. * fix: fix unnecessary code. * fix: fix typo. * fix: use relative path. * fix: fix typo. * fix: fix link.
		
			
				
	
	
		
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			43 lines
		
	
	
	
		
			2.9 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
# Orca Quickstarts
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- [**TensorFlow 2 Quickstart**](./orca-tf2keras-quickstart.html)
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    > [Run in Google Colab](https://colab.research.google.com/github/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/tf2_keras_lenet_mnist.ipynb)  [View source on GitHub](https://github.com/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/tf2_keras_lenet_mnist.ipynb)
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    In this guide we will describe how to scale out TensorFlow 2 programs using Orca in 5 simple steps.
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- [**PyTorch Quickstart**](./orca-pytorch-quickstart.html)
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    > [Run in Google Colab](https://colab.research.google.com/github/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/pytorch_lenet_mnist.ipynb)  [View source on GitHub](https://github.com/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/pytorch_lenet_mnist_spark.ipynb)
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    In this guide we will describe how to scale out PyTorch programs using Orca in 5 simple steps.
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- [**RayOnSpark Quickstart**](./ray-quickstart.html)
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    > [Run in Google Colab](https://colab.research.google.com/github/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/ray_parameter_server.ipynb)  [View source on GitHub](https://github.com/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/ray_parameter_server.ipynb)
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    In this guide we will describe how to use RayOnSpark to directly run Ray programs on Big Data clusters in 2 simple steps.
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- [**TensorFlow 1.15 Quickstart**](./orca-tf-quickstart.html)
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    > [Run in Google Colab](https://colab.research.google.com/github/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/tf_lenet_mnist.ipynb)  [View source on GitHub](https://github.com/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/tf_lenet_mnist.ipynb)
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    In this guide we will describe how to scale out TensorFlow 1.15 programs using Orca in 4 simple steps.
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- [**Keras 2.3 Quickstart**](./orca-keras-quickstart.html)
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    > [Run in Google Colab](https://colab.research.google.com/github/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/keras_lenet_mnist.ipynb)  [View source on GitHub](https://github.com/intel-analytics/BigDL/blob/main/python/orca/colab-notebook/quickstart/keras_lenet_mnist.ipynb)
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    In this guide we will describe how to scale out Keras 2.3 programs using Orca in 4 simple steps.
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