ML.NET is a machine learning framework built for .NET developers.
Use your .NET and C# or F# skills to easily integrate custom machine learning into your applications without any prior expertise in developing or tuning machine learning models.
ML.NET is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers.
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, all in .NET.
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, PowerPoint, 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. 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 ML data structures.
To learn more: Microsoft Announcement
Source @GitHub Samples @GitHub
Get started with ML.NET in 10 minutes @Microsoft
Microsoft has released the final version of .Net Core 2.0 yesterday and it is ready for production workloads. Along with this the following core frameworks are also announced on their general availability with their final releases.
ASP.NET Core 2.0
Entity Framework Core 2.0
.NET Standard 2.0
You can also watch the launch video on Channel 9 to see many of the new features in action.
To download the .NET Core Framework, SDK and runtime visit here.
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A first-hand look from the .NET engineering teams