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Microsoft's ML.NET Machine Learning Framework Now a Release Candidate

Microsoft shipped its open source, cross-platform machine learning framework, ML.NET, as a Release Candidate, just one step away from general availability.

ML.NET helps .NET coders put their C# and F# skills to work in developing and integrating custom machine learning models into Web, mobile, desktop, gaming and Internet of Things (IoT) applications.

Just last month, Microsoft announced ML.NET 0.11, described as a stability release, with the promise of providing help to enterprises wishing to get it set up for production use.

That production-usage goal gets a step closer with the ML.NET 1.0 RC release, which finishes off changes to the main APIs. From here on, Microsoft said, the goal is to improve documentation and samples, and deal with any critical issues that arise -- all without introducing any breaking changes before general availability, expected soon.

"Soon we will be ending the first main milestone of a great journey in the open that started on May 2018 when releasing ML.NET 0.1 as open source," Microsoft said in an announcement last week. "Since then we’ve been releasing monthly, 12 preview releases so far."

Updates in the RC include:

  • Segregation of stable vs. preview version of ML.NET packages: Heading toward ML.NET 1.0, most of the functionality in ML.NET (around 95 percent) is going to be released as stable (version 1.0).
  • IDataView moved to Microsoft.ML namespace: Microsoft moved IDataView back into Microsoft.ML namespace based on developer feedback.
  • TensorFlow-support fixes: Some issues in v0.11 were addressed regarding support for TensorFlow, an open source machine learning framework used for deep learning scenarios (such as computer vision and natural language processing).

The full release notes detail all of the above and many more changes.

ML.NET is expected to hit general availability in the second quarter of the 2019 calendar year. As that includes the April-June timespan -- and releases have been cranked out in a regular monthly cadence going back a year -- developers should watch for the final product to debut next month.

And the company renewed its offer for help organizations take an ML.NET app into production, stating they can talk to an ML.NET engineer to:

  • Get help implementing ML.NET successfully in an application.
  • Provide feedback about ML.NET.
  • Demo an app and potentially have it featured on the ML.NET homepage, .NET Blog, or other Microsoft channel.

Interested organizations and developers can apply for that help here.

About the Author

David Ramel is an editor and writer at Converge 360.

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