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@@ -23,7 +23,7 @@ Machine Learning notebook samples and encourage efficient retrieval of topics an
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|[Setup automated ML SQL integration](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/automated-machine-learning/sql-server/setup/auto-ml-sql-setup.ipynb)| None | None | None | None | Azure ML AutoML ||
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|[Register a model and deploy locally](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/deployment/deploy-to-local/register-model-deploy-local.ipynb)| Deployment | None | local | Local | None | None |
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|:star:[Data drift on aks](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/monitor-models/data-drift/drift-on-aks.ipynb)| Filtering | NOAA | remote | AKS | Azure ML | Dataset, Timeseries, Drift |
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|[](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/training/train-within-notebook/train-within-notebook.ipynb)| Training and deploying a model from a notebook | Diabetes | Local | Azure Container Instance | None | None |
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|[Training and deploying a model from a notebook](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/training/train-within-notebook/train-within-notebook.ipynb)| Training and deploying a model from a notebook | Diabetes | Local | Azure Container Instance | None | None |
|:star:[Filtering data using Tabular Timeseiries Dataset related API](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/work-with-data/datasets-tutorial/tabular-timeseries-dataset-filtering.ipynb)| Filtering | NOAA | local | None | Azure ML | Dataset, Tabular Timeseries |
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|:star:[Train with Datasets (Tabular and File)](https://github.com/Azure/MachineLearningNotebooks/blob/master//how-to-use-azureml/work-with-data/datasets-tutorial/train-with-datasets.ipynb)| Filtering | Iris, Daibetes | remote | None | Azure ML | Dataset |
@@ -99,7 +99,7 @@ Machine Learning notebook samples and encourage efficient retrieval of topics an
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