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Microsoft Open Sources Their Infer.NET Machine Learning Framework

Microsoft Open Sources Their Infer.NET Machine Learning Framework


The Infer.NET Team. (Top row, left to right) Martin Kukla, John Guiver, Tom Minka, John Winn, Sam Webster, Dany Fabian. (Bottom row, left to right) Pavel Myshkov, Yordan Zaykov, Alex Spengler.

Tech giant Microsoft made the decision to announce that one of the top-tier cross-platform frameworks for model-based machine learning is open to one and all worldwide. “We’re extremely excited today to open source Infer.NET on GitHub under the permissive MIT license for free use in commercial applications,” wrote Yordan Zaykov, Principal Research Software Engineering Lead at Microsoft in an official statement.

Open sourcing Infer.NET represents the culmination of a long and ambitious journey. The Microsoft Research Team in Cambridge embarked on developing the framework back in 2004. The statement said that they had learned a lot along the way about making ML solutions that are scalable and interpretable.



“Infer.NET initially was envisioned as a research tool and we released it for academic use in 2008. As a result, there have been hundreds of papers published using the framework across a variety of fields, everything from information retrieval to healthcare… Over time, the framework has evolved from a research tool to being the ML engine in a number of Microsoft products in Office, Xbox and Azure,” they said

The Infer.NET team now reportedly looking forward to engaging with the open source community in developing and growing the framework further. Infer.NET will become a part of ML.NET – the machine learning framework for .NET developers. Microsoft has already taken several steps towards integration with ML.NET, like setting up the repository under the .NET Foundation and moving the package and namespaces to Microsoft.ML.Probabilistic. Infer.NET will extend ML.NET for statistical modelling and online learning.

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Last month, Microsoft had integrated Python, the programming language widely used by statisticians, data scientists, and data analysts, into their business intelligence software.


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