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Merge pull request #159 from jeff-shepherd/master
Removed databricks notebook link
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how-to-use-azureml/automated-machine-learning/README.md

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@@ -35,7 +35,7 @@ Below are the three execution environments supported by AutoML.
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**NOTE**: You should at least have contributor access to your Azure subcription to run the notebook.
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- Please remove the previous SDK version if there is any and install the latest SDK by installing **azureml-sdk[automl_databricks]** as a PyPi library in Azure Databricks workspace.
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- You can find the detail Readme instructions at [GitHub](https://github.com/Azure/MachineLearningNotebooks/tree/master/how-to-use-azureml/azure-databricks).
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- Download the sample notebook AutoML_Databricks_local_06.ipynb from [GitHub](https://github.com/Azure/MachineLearningNotebooks/tree/master/how-to-use-azureml/azure-databricks) and import into the Azure databricks workspace.
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- Download the sample notebook automl-databricks-local-01.ipynb from [GitHub](https://github.com/Azure/MachineLearningNotebooks/tree/master/how-to-use-azureml/azure-databricks) and import into the Azure databricks workspace.
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- Attach the notebook to the cluster.
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<a name="localconda"></a>
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- [auto-ml-dataprep-remote-execution.ipynb](dataprep-remote-execution/auto-ml-dataprep-remote-execution.ipynb)
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- Using DataPrep for reading data with remote execution
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- [auto-ml-classification-local-azuredatabricks.ipynb](classification-local-azuredatabricks/auto-ml-classification-local-azuredatabricks.ipynb)
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- Dataset: scikit learn's [digit dataset](https://innovate.burningman.org/datasets-page/)
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- Example of using AutoML for classification using Azure Databricks as the platform for training
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- [auto-ml-classification-with-whitelisting.ipynb](classification-with-whitelisting/auto-ml-classification-with-whitelisting.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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- Simple example of using Auto ML for classification with whitelisting tensorflow models.

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