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Fixed links to configuration notebook.
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@@ -25,7 +25,7 @@ Below are the three execution environments supported by AutoML.
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1. [](https://aka.ms/aml-clone-azure-notebooks)
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[Import sample notebooks ](https://aka.ms/aml-clone-azure-notebooks) into Azure Notebooks.
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1. Follow the instructions in the [configuration](configuration.ipynb) notebook to create and connect to a workspace.
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1. Follow the instructions in the [configuration](../../configuration.ipynb) notebook to create and connect to a workspace.
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1. Open one of the sample notebooks.
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<a name="databricks"></a>
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@@ -90,7 +90,7 @@ bash automl_setup_linux.sh
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```
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### 4. Running configuration.ipynb
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- Before running any samples you next need to run the configuration notebook. Click on configuration.ipynb notebook
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- Before running any samples you next need to run the configuration notebook. Click on [configuration](../../configuration.ipynb) notebook
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- Execute the cells in the notebook to Register Machine Learning Services Resource Provider and create a workspace. (*instructions in notebook*)
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### 5. Running Samples
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@@ -99,9 +99,6 @@ bash automl_setup_linux.sh
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<a name="samples"></a>
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# Automated ML SDK Sample Notebooks
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- [configuration.ipynb](configuration.ipynb)
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- Create new Azure ML Workspace
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- Save Workspace configuration file
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- [auto-ml-classification.ipynb](classification/auto-ml-classification.ipynb)
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- Dataset: scikit learn's [digit dataset](http://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits)
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@@ -169,6 +166,9 @@ bash automl_setup_linux.sh
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- How to specifying sample_weight
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- The difference that it makes to test results
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- [auto-ml-subsampling-local.ipynb](subsampling/auto-ml-subsampling-local.ipynb)
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- How to enable subsampling
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- [auto-ml-dataprep.ipynb](dataprep/auto-ml-dataprep.ipynb)
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- Using DataPrep for reading data
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