Merge pull request #95528 from harneetvirk/master

AzureML Python SDK 2019-11-11 Release Notes

Author: PRMerger18

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

@@ -18,7 +18,54 @@ In this article, learn about Azure Machine Learning releases.  For the full SDK
 
 See [the list of known issues](resource-known-issues.md) to learn about known bugs and workarounds.
 
+## 2019-11-11
 
+### Azure Machine Learning SDK for Python v1.0.74
+ 
+  + **Preview features**
+    + **azureml-contrib-dataset**
+      + After importing azureml-contrib-dataset, you can call `Dataset.Labeled.from_json_lines` instead of `._Labeled` to create a labeled dataset.
+      + When calling `to_pandas_dataframe` on a labeled dataset with the download option, you can now specify whether to overwrite existing files or not.
+      + When calling `keep_columns` or `drop_columns` that results in a timeseries, label, or image column being dropped, the corresponding capabilities will be dropped for the dataset as well.
+      + Fixed issues with PyTorch loader when calling `dataset.to_torchvision()`.
+
++ **Bug fixes and improvements**
+  + **azure-cli-ml**
+    + Added Model Profiling to the preview CLI.
+    + Fixes breaking change in Azure Storage causing AzureML CLI to fail.
+    + Added Load Balancer Type to MLC for AKS types
+  + **azureml-automl-core**
+    + Fixed the issue with detection of maximal horizon on time series, having missing values and multiple grains.
+    + Fixed the issue with failures diring generation of cross validation splits.
+    + 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.
+    + Fixed the issue with masking of some user information during logging. -Improved logging of the errors during forecasting runs.
+    + Adding psutil as a conda dependency to the auto-generated yml deployment file.
+  + **azureml-contrib-mir**
+    + Fixes breaking change in Azure Storage causing AzureML CLI to fail.
+  + **azureml-core**
+    + Fixes a bug which caused models deployed on Azure Functions to produce 500s.
+    + Fixed an issue where the amlignore file was not applied on snapshots.
+    + Added a new API amlcompute.get_active_runs that returns a generator for running and queued runs on a given amlcompute.
+    + Added Load Balancer Type to MLC for AKS types.
+    + 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
+    + Fix deserialization issue for `run_config.yml` with dataset usage.
+    + When calling `keep_columns` or `drop_columns` that results in a timeseries column being dropped, the corresponding capabilities will be dropped for the dataset as well.
+  + **azureml-interpret**
+    + Updated interpret-community version to 0.1.0.3
+  + **azureml-train-automl**
+    + Fixed an issue where automl_step might not print validation issues.
+    + Fixed register_model to succeed even if the model's environment is missing dependencies locally.
+    + Fixed an issue where some remote runs were not docker enabled.
+    + Add logging of the exception that is causing a local run to fail prematurely.
+  + **azureml-train-core**
+    + Consider resume_from runs in the calculation of automated hyperparameter tuning best child runs.
+  + **azureml-pipeline-core**
+    + Fixed parameter handling in pipeline argument construction.
+    + Added pipeline description and step type yaml parameter.
+    + New yaml format for Pipeline step and added deprecation warning for old format.
+    
+    
+  
 ## 2019-11-04
 
 ### Web experience