From 96299daab82f7ccd8c495acb74e2e585ee8a3c67 Mon Sep 17 00:00:00 2001
From: Gary Ericson <garye@microsoft.com>
Date: Wed, 7 Jan 2015 12:39:49 -0800
Subject: [PATCH] Updating master from sand-01-07-15b

---
 articles/machine-learning-create-experiment.md         | 4 ++--
 articles/machine-learning-walkthrough-2-upload-data.md | 2 +-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/articles/machine-learning-create-experiment.md b/articles/machine-learning-create-experiment.md
index 120b565e900..99f49c794c7 100644
--- a/articles/machine-learning-create-experiment.md
+++ b/articles/machine-learning-create-experiment.md
@@ -1,6 +1,6 @@
 <properties title="Create a simple experiment in Azure Machine Learning Studio" pageTitle="Create a simple experiment in Machine Learning Studio | Azure" description="How to create an experiment to train and test a simple model in Azure Machine Learning Studio" metaKeywords="" services="machine-learning" solutions="" documentationCenter="" authors="garye" manager="paulettm" editor="cgronlun"  videoId="" scriptId="" />
 
-<tags ms.service="machine-learning" ms.workload="data-services" ms.tgt_pltfrm="na" ms.devlang="na" ms.topic="article" ms.date="08/22/2014" ms.author="garye" />
+<tags ms.service="machine-learning" ms.workload="data-services" ms.tgt_pltfrm="na" ms.devlang="na" ms.topic="article" ms.date="01/07/2015" ms.author="garye" />
 
 #Create a simple experiment in Azure Machine Learning Studio 
  
@@ -57,7 +57,7 @@ A dataset usually requires some pre-processing before it can be analyzed. You ma
 
 First we'll remove the "normalized-losses" column, and then we'll remove any row that has missing data. 
 
-1. Type "project columns" in the search box at the top of this palette to find the **Project Columns** module, then drag it to the experiment canvas and connect it to the output port of the **Automobile price data (Raw)** dataset. This module allows us to select which columns of data we want to include or exclude in the model. 
+1. Type "project columns" in the search box at the top of the module palette to find the **Project Columns** module, then drag it to the experiment canvas and connect it to the output port of the **Automobile price data (Raw)** dataset. This module allows us to select which columns of data we want to include or exclude in the model. 
 
 2. Select the **Project Columns** module and click **Launch column selector** in the properties pane. 
 
diff --git a/articles/machine-learning-walkthrough-2-upload-data.md b/articles/machine-learning-walkthrough-2-upload-data.md
index 93586d4c1d1..c8f3afc1b70 100644
--- a/articles/machine-learning-walkthrough-2-upload-data.md
+++ b/articles/machine-learning-walkthrough-2-upload-data.md
@@ -1,6 +1,6 @@
 <properties title="Step 2: Upload existing data into an Azure Machine Learning experiment" pageTitle="Step 2: Upload data into a Machine Learning experiment | Azure" description="Step 2: Upload existing public data into Azure Machine Learning Studio" metaKeywords="" services="machine-learning" solutions="big-data" documentationCenter="" authors="garye" videoId="" scriptId="" manager="paulettm" editor="cgronlun" />
 
-<tags ms.service="machine-learning" ms.workload="tbd" ms.tgt_pltfrm="na" ms.devlang="na" ms.topic="article" ms.date="09/02/2014" ms.author="garye" />
+<tags ms.service="machine-learning" ms.workload="tbd" ms.tgt_pltfrm="na" ms.devlang="na" ms.topic="article" ms.date="01/06/2015" ms.author="garye" />
 
 This is the second step of the walkthrough, [Developing a Predictive Solution with Azure ML][develop]: