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articles/machine-learning/service/azure-machine-learning-release-notes.md

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@@ -25,7 +25,7 @@ See [the list of known issues](resource-known-issues.md) to learn about known bu
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### Azure Machine Learning SDK for Python v1.0.43
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+ **New features**
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+ Azure Machine Learning now provides first-class support for popular machine learning and data analysis framework Scikit-learn. Using [`SKLearn` estimator](https://docs.microsoft.com/en-us/python/api/azureml-train-core/azureml.train.sklearn.sklearn?view=azure-ml-py), users can easily train and deploy Scikit-learn models.
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+ Azure Machine Learning now provides first-class support for popular machine learning and data analysis framework Scikit-learn. Using [`SKLearn` estimator](https://docs.microsoft.com/python/api/azureml-train-core/azureml.train.sklearn.sklearn?view=azure-ml-py), users can easily train and deploy Scikit-learn models.
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+ Learn how to [run hyperparameter tuning with Scikit-learn using HyperDrive](https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/training/train-hyperparameter-tune-deploy-with-sklearn/train-hyperparameter-tune-deploy-with-sklearn.ipynb).
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+ Added support for creating ModuleStep in pipelines along with Module and ModuleVersion classes to manage reusable compute units.
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+ ACI webservices now support persistent scoring_uri through updates. The scoring_uri will change from IP to FQDN. The Dns Name Label for FQDN can be configured by setting the dns_name_label on deploy_configuration.
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+ Moved outputs directory creation and outputs directory upload out of the user process. Enabled run history SDK to run in every user process. This should resolve some synchronization issues experienced by distributed training runs.
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+ The name of the azureml log written from the user process name will now include process name (for distributed training only) and PID.
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## 2019-06-10
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### Azure Machine Learning Data Prep SDK v1.1.5
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+ **Bug fixes and improvements**

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