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articles/machine-learning/how-to-monitor-tensorboard.md

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@@ -37,8 +37,8 @@ How you launch TensorBoard with Azure Machine Learning experiments depends on th
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* Azure Machine Learning compute instance - no downloads or installation necessary
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* Complete the [Quickstart: Get started with Azure Machine Learning](quickstart-create-resources.md) to create a dedicated notebook server pre-loaded with the SDK and the sample repository.
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* In the samples folder on the notebook server, find two completed and expanded notebooks by navigating to these directories:
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* **how-to-use-azureml > track-and-monitor-experiments > tensorboard > export-run-history-to-tensorboard > export-run-history-to-tensorboard.ipynb**
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* **how-to-use-azureml > track-and-monitor-experiments > tensorboard > tensorboard > tensorboard.ipynb**
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* **v1 (<version>) > how-to-use-azureml > track-and-monitor-experiments > tensorboard > export-run-history-to-tensorboard > export-run-history-to-tensorboard.ipynb**
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* **v1 (<version>) > how-to-use-azureml > track-and-monitor-experiments > tensorboard > tensorboard > tensorboard.ipynb**
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* Your own Juptyer notebook server
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* [Install the Azure Machine Learning SDK](/python/api/overview/azure/ml/install) with the `tensorboard` extra
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* [Create an Azure Machine Learning workspace](quickstart-create-resources.md).

articles/machine-learning/v1/how-to-use-reinforcement-learning.md

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@@ -37,8 +37,8 @@ Run this code in either of these environments. We recommend you try Azure Machin
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- Azure Machine Learning compute instance
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- Learn how to clone sample notebooks in [Tutorial: Train and deploy a model](../tutorial-train-deploy-notebook.md).
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- Clone the **how-to-use-azureml** folder instead of **tutorials**
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- Learn how to clone sample notebooks in [Tutorial: Train and deploy a model](tutorial-train-deploy-notebook.md).
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- Clone the **v1 (<version>) > how-to-use-azureml** folder instead of **tutorials**
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- Run the virtual network setup notebook located at `/how-to-use-azureml/reinforcement-learning/setup/devenv_setup.ipynb` to open network ports used for distributed reinforcement learning.
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- Run the sample notebook `/how-to-use-azureml/reinforcement-learning/atari-on-distributed-compute/pong_rllib.ipynb`
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articles/machine-learning/v1/tutorial-train-deploy-notebook.md

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You complete the following experiment setup and run steps in Azure Machine Learning studio. This consolidated interface includes machine learning tools to perform data science scenarios for data science practitioners of all skill levels.
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[!INCLUDE [clone repo v1](../../../includes/machine-learning-clone-v1-repo.md)]
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1. Sign in to [Azure Machine Learning studio](https://ml.azure.com/).
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1. Select your subscription and the workspace you created.
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1. On the left, select **Notebooks**.
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1. At the top, select the **Samples** tab.
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1. Open the **v1 (<version>)** folder. The version number represents the current v1 release for the Python SDK.
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1. Select the **...** button at the right of the **tutorials** folder, and then select **Clone**.
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:::image type="content" source="media/tutorial-1st-experiment-sdk-setup/clone-tutorials.png" alt-text="Screenshot that shows the Clone tutorials folder.":::
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1. A list of folders shows each user who accesses the workspace. Select your folder to clone the **tutorials** folder there.
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## Open the cloned notebook
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1. Open the **MachineLearningNotebooks** folder that was cloned into your **Files** section.
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1. Open the **tutorials** folder that was cloned into your **User files** section.
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1. Select the **quickstart-azureml-in-10mins.ipynb** file from your **MachineLearningNotebooks/tutorials/compute-instance-quickstarts/quickstart-azureml-in-10mins** folder.
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1. Select the **quickstart-azureml-in-10mins.ipynb** file from your **tutorials/compute-instance-quickstarts/quickstart-azureml-in-10mins** folder.
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:::image type="content" source="media/tutorial-train-deploy-notebook/expand-folder.png" alt-text="Screenshot shows the Open tutorials folder.":::
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