updates for freshness

Author: Larry Franks

articles/machine-learning/concept-azure-machine-learning-architecture.md

@@ -25,9 +25,9 @@ Learn about the architecture, concepts, and workflow for Azure Machine Learning.
 The machine learning model workflow generally follows this sequence:
 
 1. **Train**
-    + Develop machine learning training scripts in **Python** or with the visual designer.
+    + Develop machine learning training scripts in **Python**, **R**, or with the visual designer.
     + Create and configure a **compute target**.
-    + **Submit the scripts** to the configured compute target to run in that environment. During training, the scripts can read from or write to **datastore**. And the records of execution are saved as **runs** in the **workspace** and grouped under **experiments**.
+    + **Submit the scripts** to a configured compute target to run in that environment. During training, the scripts can read from or write to **datastores**. The logs and output produced during training are saved as **runs** in the **workspace** and grouped under **experiments**.
 
 1. **Package** - After a satisfactory run is found, register the persisted model in the **model registry**.
 

includes/machine-learning-service-install-extension.md

@@ -2,7 +2,7 @@
 author: Blackmist
 ms.service: machine-learning
 ms.topic: include
-ms.date: 11/06/2019
+ms.date: 03/17/2020
 ms.author: larryfr
 ---