 | |
| Original author(s) | Microsoft Research |
|---|---|
| Developer(s) | Microsoft, .NET Foundation |
| Initial release | 2008 |
| Stable release | v0.3.1912.0403[1]
/ December 4, 2019 |
| Repository | github |
| Written in | C# |
| Operating system | Microsoft Windows, macOS, Linux |
| Platform | .NET Framework, .NET, Mono |
| Type | Machine learning software library |
| License | MIT License |
| Website | dotnet |
Infer.NET is a free and open source .NET software library for machine learning.[2] It supports running Bayesian inference in graphical models and can also be used for probabilistic programming.
Overview[edit]
Infer.NET follows a model-based approach and is used to solve different kinds of machine learning problems including standard problems like classification, recommendation or clustering, customized solutions and domain-specific problems. The framework is used in various different domains such as bioinformatics, epidemiology, computer vision, and information retrieval.[3][4]
Development of the framework was started by a team at Microsoft’s research centre in Cambridge, UK in 2004. It was first released for academic use in 2008 and later open sourced in 2018.[4] In 2013, Microsoft was awarded the USPTO’s Patents for Humanity Award in Information Technology category for Infer.NET and the work in advanced machine learning techniques.[5][6]
Infer.NET is used internally at Microsoft as the machine learning engine in some of their products such as Office, Azure, and Xbox.[7]
The source code is licensed under MIT License and available on GitHub.[8] It is also available as NuGet package.[9]
See also[edit]
References[edit]
- ^ "dotnet/infer". GitHub.
- ^ "Microsoft's popular machine learning framework Infer.NET goes open source".
- ^ Bandyopadhyay, Avimanyu. "Microsoft Open Sources Infer.NET AI Framework [For Humanity]".
- ^ a b Speed, Richard. "Microsoft open-sources Infer.NET AI code just in time for the weekend". www.theregister.com.
- ^ "2013 Award Recipients". www.uspto.gov.
- ^ "Microsoft Wins "Patents for Humanity" Award For Infer.NET From USPTO".
- ^ Krill, Paul (October 9, 2018). "Microsoft open-sources Infer.Net model-based machine learning". InfoWorld.
- ^ "dotnet/infer". November 3, 2020 – via GitHub.
- ^ "Infer.Net 2.4.0". www.nuget.org.
Further reading[edit]
- Knowles, D.; Parts, L.; Glass, D.; Winn, John (2010). "Modeling skin and ageing phenotypes using latent variable models in Infer.NET" (PDF).
{{cite journal}}: Cite journal requires|journal=(help) - Winn, John; Minka, Tom (2009). "Probabilistic Programming with Infer.NET".
{{cite journal}}: Cite journal requires|journal=(help) - Winn, John; Simpson, Angela; Custovic, Adnan; Y. F. Tan, Vincent (2008). "Immune System Modeling with Infer.NET" (PDF).
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External links[edit]
- Infer.NET
- GitHub - dotnet/infer
- Machine Intelligence and Perception - Microsoft Research
- Infer.NET - Practical Implementation Issues and a Comparison of Approximation Techniques
