F# is well-suited to machine learning because of its efficient execution, succinct style, data access capabilities and scalability. F# has been successfully used by some of the most advanced machine learning teams in the world, including several groups at Microsoft Research.

Try F# has some introductory machine learning algorithms. Further resources related to different aspects of machine learning are below.

Related material also exists in other Guides. For detailed information, refer to the guides for:

This guide includes resources related to machine learning programming with F#. To contribute to this guide, log on to GitHub, edit this page and send a pull request.

Note that the resources listed below are provided only for educational purposes related to the F# programming language. The F# Software Foundation does not endorse or recommend any commercial products, processes, or services. Therefore, mention of commercial products, processes, or services should not be construed as an endorsement or recommendation.

Resources for Machine Learning

Tutorials and Introductions

Introductions to different machine learning algorithms with F#:

Machine Learning Packages

Several F# machine learning packages are available. Some are accessed through F#’s interoperability mechanisms to R, Python and Java. .NET packages can be found by searching on nuget.org. For example: