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articles/machine-learning/tutorial-1st-experiment-sdk-setup.md

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> [!IMPORTANT]
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> You can view notebooks in the **samples** folder but you cannot run a notebook from there. In order to run a notebook, make sure you open the cloned version of the notebook in the **User Files** section.
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1. Select the **tutorial-1st-experiment-sdk-train.ipynb** file in your **tutorials** folder.
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1. Select the **tutorial-1st-experiment-sdk-train.ipynb** file in your **tutorials/create-first-ml-experiment** folder.
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1. On the top bar, select a compute instance to use to run the notebook. These VMs are pre-configured with [everything you need to run Azure Machine Learning](concept-compute-instance.md#contents). You can select a VM created by any user of your workspace.
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articles/machine-learning/tutorial-1st-experiment-sdk-train.md

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ms.date: 02/03/2020
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# Tutorial: Train your first ML model

articles/machine-learning/tutorial-auto-train-models.md

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# Tutorial: Use automated machine learning to predict taxi fares

articles/machine-learning/tutorial-deploy-models-with-aml.md

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# As a professional data scientist, I can deploy the model previously trained in tutorial1.
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articles/machine-learning/tutorial-pipeline-batch-scoring-classification.md

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# Tutorial: Build an Azure Machine Learning pipeline for batch scoring

articles/machine-learning/tutorial-train-models-with-aml.md

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#Customer intent: As a professional data scientist, I can build an image classification model with Azure Machine Learning by using Python in a Jupyter notebook.
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