Metadata and sentiment analysis tutorial updates (#78)

* updates

* old feedback from Bill

* added links

* added blog post title

Author: mairaw

docs/machine-learning/index.md

@@ -1,23 +1,18 @@
 ---
 title: ML.NET Guide
-description: Learn how the ML.NET Guide can help you understand how to build custom AI solutions and integrate them into your .NET applications.
+description: Learn how to build custom AI solutions and integrate them into your .NET applications using ML.NET.
 author: aditidugar
-ms.author: johalex
 ms.date: 05/07/2018
-ms.topic: conceptual
-ms.prod: dotnet-ml
-ms.devlang: dotnet
-manager: wpickett
 ---
 # ML.NET Guide
 
 ML.NET is a free, open-source, and cross-platform machine learning framework that enables you to build custom machine learning solutions and integrate them into your .NET applications. This guide provides many resources about working with ML.NET.
 
-For more information about ML.NET, visit our [What is ML.NET]() page.
+For more information about ML.NET, see [ntroducing ML.NET: Cross-platform, Proven and Open Source Machine Learning Framework ](https://blogs.msdn.microsoft.com/dotnet/) post on the .NET blog.
 
 ## Get started
 
-To get started with ML.NET, check out the [Iris Petal Prediction quickstart]() or the more in-depth [tutorials](tutorials/index.md).
+To get started with ML.NET, check out the [Iris Petal Prediction quickstart](https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet/get-started) or the more in-depth [tutorials](tutorials/index.md).
 
 If you are new to machine learning, you can also review the [Machine Learning Basics](resources/basics.md), where you'll find machine learning resources to assist you.
 
@@ -26,14 +21,13 @@ If you are new to machine learning, you can also review the [Machine Learning Ba
 There are several sections in the ML.NET Guide. You can read them in order, or jump directly to what interests you the most.
 
 **[Tutorials](tutorials/index.md)**
-   
 
-In this section you will find step-by-step tutorials that will guide you through building custom machine learning models for common developer scenarios. 
+In this section, you find step-by-step tutorials that guide you through building custom machine learning models for common developer scenarios.
 
 **[Glossary](resources/glossary.md)**
-  
- Find a list of Machine Learning terminology and their definitions.
 
-## See also
+Find a list of machine learning terminology and their definitions.
+
 ## API reference
-Check out the [ML.NET API Reference](https://github.com/dotnet/ml-api-docs) to see the breadth of APIs available.
+
+Check out the [ML.NET API Reference](https://docs.microsoft.com/dotnet/api/?view=ml-dotnet) to see the breadth of APIs available.

docs/machine-learning/tutorials/flight-delay.md

@@ -1,17 +1,14 @@
 ---
 title: Use ML.NET in a regression scenario.
 description: Learn how to use ML.NET in a regression scenario.
-ms.prod: dotnet-ml
-ms.devlang: dotnet
-ms.author: johalex
 author: aditidugar
 ms.date: 05/07/2018
 ms.topic: tutorial
-manager: wpickett
 ms.custom: mvc
 #Customer intent: As a < type of user >, I want < what? > so that < why? >.
 ---
-# Tutorial: Use ML.NET in a regression scenario.
+# Tutorial: Use ML.NET in a regression scenario
+
 Introductory paragraph that ends with: if you don't have an Azure subscription, [create a free account](https://azure.microsoft.com/free/) before you begin.
 
 In this tutorial, you learn how to:

docs/machine-learning/tutorials/index.md

@@ -1,18 +1,11 @@
 ---
-title: ML.NET Tutorials
+title: ML.NET tutorials
 description: Explore these ML.NET tutorials to learn how to build custom AI solutions and integrate them into your .NET applications.
-author: jralexander
-ms.author: johalex
 ms.date: 05/07/2018
-ms.topic: conceptual
-ms.prod: dotnet-ml
-ms.devlang: dotnet
-manager: wpickett
-#Customer intent: As a developer, I want < what? > so that < why? >.
 ---
-# ML.NET Tutorials
+# ML.NET tutorials
 
-The following tutorials enable you to understand how to use [ML.NET](../index.md) to build custom machine learning solutions and integrate them into your .NET applications.
+The following tutorials enable you to understand how to use [ML.NET](../index.md) to build custom machine learning solutions and integrate them into your .NET applications:
 
 * [Sentiment Analysis](sentiment-analysis.md): demonstrates how to apply a binary classification task using ML.NET.
 * [Flight Delay Predicion](flight-delay.md): demonstrates how to apply a regression task using ML.NET.