Merge pull request #106577 from j-martens/master

freshness and formatting fixes

Author: GitHubber17

articles/machine-learning/algorithm-cheat-sheet.md

@@ -9,7 +9,7 @@ ms.topic: conceptual
 
 author: FrancescaLazzeri
 ms.author: lazzeri
-ms.date: 11/04/2019
+ms.date: 03/05/2020
 ---
 # Machine Learning Algorithm Cheat Sheet for Azure Machine Learning designer
 

articles/machine-learning/concept-deep-learning-vs-machine-learning.md

@@ -8,7 +8,7 @@ ms.subservice: core
 ms.topic: conceptual
 ms.author: lazzeri
 author: FrancescaLazzeri
-ms.date: 11/04/2019
+ms.date: 03/05/2020
 ---
 
 # Deep learning vs. machine learning

articles/machine-learning/how-to-auto-train-forecast.md

@@ -113,7 +113,7 @@ For forecasting tasks, automated machine learning uses pre-processing and estima
 
 The [`AutoMLConfig`](https://docs.microsoft.com/python/api/azureml-train-automl-client/azureml.train.automl.automlconfig.automlconfig?view=azure-ml-py) object defines the settings and data necessary for an automated machine learning task. Similar to a regression problem, you define standard training parameters like task type, number of iterations, training data, and number of cross-validations. For forecasting tasks, there are additional parameters that must be set that affect the experiment. The following table explains each parameter and its usage.
 
-| Param | Description | Required |
+| Parameter name | Description | Required |
 |-------|-------|-------|
 |`time_column_name`|Used to specify the datetime column in the input data used for building the time series and inferring its frequency.|✓|
 |`grain_column_names`|Name(s) defining individual series groups in the input data. If grain is not defined, the data set is assumed to be one time-series.||

articles/machine-learning/how-to-select-algorithms.md

@@ -10,7 +10,7 @@ ms.topic: conceptual
 author: FrancescaLazzeri
 ms.author: lazzeri
 ms.reviewer: cgronlun
-ms.date: 01/21/2020
+ms.date: 03/05/2020
 ---
 # How to select algorithms for Azure Machine Learning
 

articles/machine-learning/index.yml

@@ -14,7 +14,7 @@ metadata:
   ms.collection: collection
   author: j-martens
   ms.author: jmartens
-  ms.date: 02/16/2020
+  ms.date: 03/05/2020
 
 # linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new
 

articles/machine-learning/overview-what-happened-to-workbench.md

@@ -9,8 +9,7 @@ ms.topic: overview
 ms.reviewer: jmartens
 author: j-martens
 ms.author: jmartens
-ms.date: 11/05/2019
-ms.custom: seodec18
+ms.date: 03/05/2020
 ---
 # What happened to Azure Machine Learning Workbench?
 
@@ -42,7 +41,7 @@ Although there are new improved CLI and SDK clients in the current release, the
 
 ## Support timeline
 
-On January 9th, 2019 support for Machine Learning Workbench, Azure Machine Learning Experimentation and Model Management accounts, and their associated SDK and CLI has ended.
+On January 9th, 2019 support for Machine Learning Workbench, Azure Machine Learning Experimentation and Model Management accounts, and their associated SDK and CLI ended.
 
 All the latest capabilities are available by using this <a href="https://docs.microsoft.com/python/api/overview/azure/ml/intro?view=azure-ml-py" target="_blank">SDK</a>, the [CLI](reference-azure-machine-learning-cli.md), and the [portal](how-to-manage-workspace.md).
 
@@ -97,4 +96,4 @@ Create your first experiment with your preferred method:
   + [Use R Markdown](tutorial-1st-r-experiment.md) 
   + [Use automated machine learning](tutorial-designer-automobile-price-train-score.md) 
   + [Use the designer's drag & drop capabilities](tutorial-first-experiment-automated-ml.md) 
-  + [Use the ML extension to the CLI](tutorial-train-deploy-model-cli.md)
+  + [Use the ML extension to the CLI](tutorial-train-deploy-model-cli.md)

articles/machine-learning/studio/index.yml

@@ -13,7 +13,7 @@ metadata:
   ms.collection: collection
   author: j-martens
   ms.author: jmartens
-  ms.date: 09/04/2019
+  ms.date: 03/05/2020
 
 # linkListType: architecture | concept | deploy | download | get-started | how-to-guide | learn | overview | quickstart | reference | tutorial | video | whats-new