Update README.md

README.md

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-# Machine Learning in .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.
 
-### Build Status
+# Machine Learning for .NET
 
-Coming soon
+[ML.NET](https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet) is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
 
-### Installation
+ML.NET allows .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models.
 
-You can install ML.NET NuGet from the CLI using:
+ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, Power Point, Excel and more.
+
+With this first preview release ML.NET enables ML tasks like classification (e.g. support text classification, sentiment analysis) and regression (e.g. forecasting, price-prediction). 
+
+Along with these ML capabilities this first release of ML.NET also brings the first draft of .NET APIs for training models, using models for predictions, as well as the core components of this framework such as learning algorithms, transforms, and core ML data structures. 
+
+ML.NET is first and foremost a  framework which means it can be extended to add popular ML Libraries like TensorFlow, Accord.NET and CNTK. The design of the framework will prioritize usability, extensibility, and toolability, without sacrificing performance.
+
+## Installation
+
+ML.NET runs on Windows, Linux, and macOS - any platform where 64 bit [.NET Core](https://github.com/dotnet/core) or later is available.
+
+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.
+
+## Contributing
+
+We welcome contributions! Please review our [contribution guide](https://github.com/dotnet/machinelearning/blob/master/CONTRIBUTING.md).
 
-### Example
+## 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 +65,7 @@ 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 +78,6 @@ 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 +88,5 @@ 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.
+