Update README.md

README.md

@@ -1,30 +1,52 @@
-# Machine Learning in .NET
+# Machine Learning for .NET
 
-ML.NET provides state-of-the-art machine learning (ML) algorithms, transforms, and components, and powers ML pipelines in many Microsoft products.  Developed and used internally at Microsoft for over 5 years, the goal is to make ML.NET useful for all developers, data scientists, and information workers and helpful in all products, services, and devices.
+[ML.NET](https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet) provides state-of-the-art machine learning (ML) algorithms, transforms, and components, and powers ML pipelines in many Microsoft products.  Developed and used internally at Microsoft for over 5 years, the goal is to make ML.NET useful for all developers, data scientists, and information workers and helpful in all products, services, and devices.
 
-### Build Status
+ML.NET runs on Windows, Linux, and macOS - any platform where 64 bit [.NET Core](https://github.com/dotnet/core) or later is available.
 
-Coming soon
+With ML.NET you can use the latest ML algorithms to create and evaluate a model from training data. Once you have a model, you can add to your app just a few lines of .NET code to make predictions from the model. 
 
-### Installation
+## Installation
 
-You can install ML.NET NuGet from the CLI using:
+The current release is 0.1. Check out the [release notes](https://github.com/dotnet/machinelearning/blob/master/Documentation/release-notes/0.1/release-0.1.md).
+
+First ensure you have installed [.NET Core 2.0](https://www.microsoft.com/net/learn/get-started) or later. ML.NET also works on the .NET Framework. Note that ML.NET currently must run in a 64 bit process.
+
+Once you have an app, you can install ML.NET NuGet from the .NET Core CLI using:
 ```
 dotnet add package Microsoft.ML
 ```
 
-From package manager:
+or from the package manager:
 ```
 Install-Package Microsoft.ML
 ```
-For an example of getting started with .NET Core, see [here](https://www.microsoft.com/net/learn/get-started).
 
-### Building
-To build ML.NET from source go to [developers guide](https://github.com/dotnet/machinelearning/blob/master/Documentation/project-docs/developer-guide.md)
+Or alternatively you can add the Microsoft.ML package from within Visual Studio's NuGet package manager.
+
+## Building
+
+To build ML.NET from source please visit our [developers guide.](https://github.com/dotnet/machinelearning/blob/master/Documentation/project-docs/developer-guide.md)
+
+Live build status is coming soon.
 
-### Example
+## Contributing
+
+We welcome contributions! Please review our [contribution guide](https://github.com/dotnet/machinelearning/blob/master/CONTRIBUTING.md).
+
+## Community
+
+Please join our community on Gitter [![Join the chat at https://gitter.im/dotnet/corefx](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/dotnet/?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
+
+This project has adopted the code of conduct defined by the [Contributor Covenant](http://contributor-covenant.org/) to clarify expected behavior in our community.
+For more information, see the [.NET Foundation Code of Conduct](https://dotnetfoundation.org/code-of-conduct).
+
+## Examples
+
+Imagine you want to predict the sale price of a house. Given a large dataset of information about other houses, including their sale prices, you can use ML.NET to create and evaluate a model. Then, you can deploy the model with your app.
+
+Here's a different example, with code, to train a model to predict sentiment from text samples. (You can see the complete sample [here](https://github.com/dotnet/machinelearning/blob/master/test/Microsoft.ML.Tests/Scenarios/Scenario3_SentimentPrediction.cs)):
 
-Simple snippet to train a model for sentiment classification (See the complete sample [here](https://github.com/dotnet/machinelearning/blob/master/test/Microsoft.ML.Tests/Scenarios/Scenario3_SentimentPrediction.cs)):
 ```C#
 var pipeline = new LearningPipeline();
 pipeline.Add(new TextLoader<SentimentData>(dataPath, separator: ","));
@@ -33,7 +55,7 @@ pipeline.Add(new FastTreeBinaryClassifier());
 var model = pipeline.Train<SentimentData, SentimentPrediction>();
 ```
 
-Infer the trained model for predictions:
+Now from the model we can make inferences (predictions):
 
 ```C#
 SentimentData data = new SentimentData
@@ -46,11 +68,6 @@ SentimentPrediction prediction = model.Predict(data);
 Console.WriteLine("prediction: " + prediction.Sentiment);
 ```
 
-### Code of Conduct
-
-This project has adopted the code of conduct defined by the [Contributor Covenant](http://contributor-covenant.org/) to clarify expected behavior in our community.
-For more information, see the [.NET Foundation Code of Conduct](https://dotnetfoundation.org/code-of-conduct).
-
 ## License
 
 ML.NET is licensed under the [MIT license](LICENSE).
@@ -61,4 +78,5 @@ ML.NET is a [.NET Foundation](http://www.dotnetfoundation.org/projects) project.
 
 There are many .NET related projects on GitHub.
 
-- [.NET home repo](https://github.com/Microsoft/dotnet) - links to 100s of .NET projects, from Microsoft and the community.
+- [.NET home repo](https://github.com/Microsoft/dotnet) - links to 100s of .NET projects, from Microsoft and the community.
+