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@@ -18,6 +18,10 @@ You can also consume both TensorFlow and ONNX models within ML.NET which makes t
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- Take a look at some [ML.NET Community Samples](https://github.com/dotnet/machinelearning-samples/blob/main/docs/COMMUNITY-SAMPLES.md).
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- Watch some videos on the [ML.NET videos YouTube playlist](https://aka.ms/mlnetyoutube).
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## Roadmap
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Take a look at ML.NET's [Roadmap](ROADMAP.md) to what the team plans to work on in the next year.
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## Operating systems and processor architectures supported by ML.NET
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ML.NET runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework.
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## Release notes
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Check out the [release notes](docs/release-notes) to see what's new.
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Check out the [release notes](docs/release-notes) to see what's new. You can also read the [blog posts](https://devblogs.microsoft.com/dotnet/category/ml-net/) for more details about each release.
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## Using ML.NET packages
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## Building ML.NET (For contributors building ML.NET open source code)
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To build ML.NET from source please visit our [developers guide](docs/project-docs/developer-guide.md).
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To build ML.NET from source please visit our [developer guide](docs/project-docs/developer-guide.md).
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## Release process and versioning
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Check out the [release process documentation](docs/release-notes) to understand the different kinds of ML.NET releases.
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Major releases of ML.NET are shipped once a year with the major .NET releases, starting with ML.NET 1.7 in November 2021 with .NET 6, then ML.NET 2.0 with .NET 7, etc. We will maintain release branches to optionally service ML.NET with bug fixes and/or minor features on the same cadence as .NET servicing.
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Check out the [Release Notes](docs/release-notes) to see all of the past ML.NET releases.
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## Contributing
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We welcome contributions! Please review our [contribution guide](CONTRIBUTING.md).
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## Community
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- Join our community on [Discord](aka.ms/dotnet-discord).
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- Join our community on [Discord](https://aka.ms/dotnet-discord).
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- Tune into the [.NET Machine Learning Community Standup](https://dotnet.microsoft.com/live/community-standup) every other Wednesday at 10AM Pacific Time.
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This project has adopted the code of conduct defined by the [Contributor Covenant](https://contributor-covenant.org/) to clarify expected behavior in our community.
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For more information, see the [.NET Foundation Code of Conduct](https://dotnetfoundation.org/code-of-conduct).
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## Code examples
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Here is a snippet code for training a model to predict sentiment from text samples. You can find complete samples in the [samples repo](https://github.com/dotnet/machinelearning-samples).
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Here is a code snippet for training a model to predict sentiment from text samples. You can find complete samples in the [samples repo](https://github.com/dotnet/machinelearning-samples).
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