.NET developers, across platforms, now have access to machine learning from their home turf. Microsoft Automated Machine Leaning (AutoML) is included, and a Model Builder extension for Visual ...

ML.NET allows .NET developers to build custom models that can be used everywhere: in the cloud, on-premises, on a device, etc without the need for switching between development languages. ML.NET can ...

And ML.NET 3.0 gains new automated machine learning (AutoML) capabilities including the AutoML Sweeper now supporting sentence similarity, question answering, and object detection.

The Data Science Lab How to Do Logistic Regression Using ML.NET Microsoft Research's Dr. James McCaffrey show how to perform binary classification with logistic regression using the Microsoft ML.NET ...

Microsoft announced the release of ML.NET 2.0, the open-source machine learning framework for .NET. The release contains several updated natural language processing (NLP) APIs, including ...

Microsoft has released the 0.6 version of its ML.Net machine learning framework, aimed at .Net developers. The update adds a new and more useful model-building API set, the ability to use more ...

At Build 2019, Microsoft previewed new Visual Studio features for remote work, unveiled the .NET roadmap, and launched ML.NET 1.0.

Earlier this month Microsoft announced ML.NET 1.2, along with updates on its Model Builder and CLI. ML.NET is an open-source, cross-platform machine learning (ML) framework for the .NET ecosystem.

Microsoft launched Visual Studio Online public preview, which meshes together Visual Studio, cloud-hosted developer environments, and a web-based editor.