Add release notes for ML.NET 0.9 (dotnet#2061)

Author: shauheen

docs/release-notes/0.9/release-0.9.md

@@ -0,0 +1,51 @@
+# ML.NET 0.9 Release Notes
+
+Welcome to 2019! For the past 9 months we have been adding features and improving [ML.NET](https://aka.ms/mlnet). In the forthcoming 0.10, 0.11, and 0.12 releases before we reach 1.0, we will focus on the overall stability of the package, continue to refine the API, increase test coverage and improve documentation. 0.9 release packs multiple fixes as well as significant clean up to the internal code of the package.
+
+### Installation
+
+ML.NET supports Windows, MacOS, and Linux. See [supported OS versions of .NET
+Core
+2.0](https://github.com/dotnet/core/blob/master/release-notes/2.0/2.0-supported-os.md)
+for more details.
+
+You can install ML.NET NuGet from the CLI using:
+```
+dotnet add package Microsoft.ML
+```
+
+From package manager:
+```
+Install-Package Microsoft.ML
+```
+
+### Release Notes
+
+Below are a few of the highlights from this release. There are many other improvements in the API.
+
+* Added Feature Contribution Calculation
+  ([#1847](https://github.com/dotnet/machinelearning/pull/1847))
+
+    * FCC can be used to compute feature contributions in addition to the overall prediction when models are evaluated.
+
+* Removed Legacy namespace that was marked obsolete
+  ([#2043](https://github.com/dotnet/machinelearning/pull/2043))
+
+* GPU support for ONNX Transform
+  ([#1922](https://github.com/dotnet/machinelearning/pull/1922))
+
+    * GPU is currently supported on 64 bit Windows
+    * Cross platform support is still being developed for this feature
+
+* `Permutation Feature Importance` now supports confidence intervals
+  ([#1844](https://github.com/dotnet/machinelearning/pull/1844))
+
+* Introducing `PredictionEngine` instead of `PredictionFunction`
+  ([#1920](https://github.com/dotnet/machinelearning/pull/1920))
+  
+### Acknowledgements
+
+Shoutout to [dhilmathy](https://github.com/dhilmathy),
+[mnboos](https://github.com/mnboos),
+[robosek](https://github.com/robosek), and the [ML.NET](https://aka.ms/mlnet) team for their
+contributions as part of this release!