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

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@@ -19,7 +19,49 @@ In this article, learn about Azure Machine Learning releases. For the full SDK r
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See [the list of known issues](resource-known-issues.md) to learn about known bugs and workarounds.
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## 2019-11-11
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### Azure Machine Learning SDK for Python v1.0.73
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+ **New features**
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+ [Insert new features below. Reference articles and/or doc pages]
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+ **Preview features**
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+ [Contrib features below]
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+ **Breaking changes**
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+ [Reference upcoming breaking changes and old API support drop date]
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+ **Bug fixes and improvements**
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+ **azure-cli-ml**
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+ Added Model Profiling to the preview CLI.
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+ Fixes breaking change in Azure Storage causing AzureML CLI to fail.
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+ Added Load Balancer Type to MLC for AKS types
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+ **azureml-automl-core**
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+ Fixed the issue with detection of maximal horizon on time series, having missing values and multiple grains.
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+ Fixed the issue with failures diring generation of cross validation splits.
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+ Replace this section with a message in markdown format to appear in the release notes: -Improved handling of short grains in the forecasting data sets.
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+ Fixed the issue with masking of some user information during logging. -Improved logging of the errors during forecasting runs.
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+ Adding psutil as a conda dependency to the auto-generated yml deployment file.
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+ **azureml-contrib-mir**
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+ Fixes breaking change in Azure Storage causing AzureML CLI to fail.
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+ **azureml-core**
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+ Fixes a bug which caused models deployed on Azure Functions to produce 500s.
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+ Fixed an issue where the amlignore file was not applied on snapshots.
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+ Added a new API amlcompute.get_active_runs that returns a generator for running and queued runs on a given amlcompute.
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+ Added Load Balancer Type to MLC for AKS types.
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+ Added append_prefix bool parameter to download_files in run.py and download_artifacts_from_prefix in artifacts_client. This flag is used to selectively flatten the origin filepath so only the file or folder name is added to the output_directory
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+ fix deserialization issue for `run_config.yml` with dataset usage.
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+ **azureml-interpret**
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+ update interpret-community version to 0.1.0.3
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+ **azureml-train-automl**
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+ Fixed an issue where automl_step might not print validation issues.
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+ Fixed register_model to succeed even if the model's environment is missing dependencies locally.
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+ Fixed an issue where some remote runs were not docker enabled.
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+ Add logging of the exception that is causing a local run to fail prematurely.
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+ **azureml-train-core**
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+ Consider resume_from runs in the calculation of automated hyperparameter tuning best child runs.
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## 2019-11-04
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### Web experience

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