ML.NET

ML.NET
Original author(s)Microsoft
Developer(s).NET Foundation
Initial release7 May 2018; 6 years ago (2018-05-07)[1]
Stable release
3.0.0 / 28 November 2023; 11 months ago (2023-11-28)
Preview release
3.0.0-preview.23511.1 / 14 October 2023; 13 months ago (2023-10-14)
Repositorygithub.com/dotnet/machinelearning/
Written inC# and C++
Operating systemLinux, macOS, Windows[2]
Platform.NET Core,
.NET Framework
TypeMachine learning library
LicenseMIT License[3]
Websitedot.net/ml

ML.NET is a free software machine learning library for the C# and F# programming languages.[4][5][6] It also supports Python models when used together with NimbusML. The preview release of ML.NET included transforms for feature engineering like n-gram creation, and learners to handle binary classification, multi-class classification, and regression tasks.[7] Additional ML tasks like anomaly detection and recommendation systems have since been added, and other approaches like deep learning will be included in future versions.[8][9]

  1. ^ Ankit Asthana (2017-05-07). "Introducing ML.NET: Cross-platform, Proven and Open Source Machine Learning Framework". blogs.msdn.microsoft.com. Retrieved 2018-05-10.
  2. ^ "ML.NET: Machine Learning made for .NET". Microsoft. Retrieved 11 May 2018.
  3. ^ at master · DotNet/MachineLearning
  4. ^ David Ramel (2018-05-08). "Open Source, Cross-Platform ML.NET Simplifies Machine Learning -- Visual Studio Magazine". Visual Studio Magazine. Retrieved 2018-05-10.
  5. ^ Kareem Anderson (2017-05-09). "Microsoft debuts ML.NET cross-platform machine learning framework". On MSFT. Retrieved 2018-05-10.
  6. ^ Ankit Asthana (2018-08-07). "Announcing ML.NET 0.4". blogs.msdn.microsoft.com. Retrieved 2018-08-08.
  7. ^ Gal Oshri (2018-05-06). "ML.NET 0.1 Release Notes". GitHub. Retrieved 2018-05-10.
  8. ^ Tiwari, Aditya (2018-05-08). "Microsoft Launches ML.NET Open Source Machine Learning Framework". Fossbytes. Retrieved 2018-05-10. Over time, it will enable other ML tasks like anomaly detection, recommendation system, and other approaches like deep learning using the benefits of added libraries.
  9. ^ "Machine learning tasks in ML.NET". Microsoft. Retrieved 26 December 2018.