ML.NET is a cross-platform open-source machine learning framework that makes machine learning accessible to .NET developers.
The official ML.NET samples are divided in three categories:
- Getting started (C#) - basic "hello world" samples for each ML task, in C#
- Getting started (F#) - basic "hello world" samples for each ML task, in F#
- Examples - examples of how you can use various ML.NET components (learners/algorithms, transforms, etc. This is the area that will be growing significantly, covering many scenarios).
- End-to-end (C#) - real world examples of web, desktop, mobile, and other applications infused with ML solutions via ML.NET APIs.
For VB.NET samples, check this external repo supported by the community (Kudos for Nukepayload2): https://github.com/Nukepayload2/machinelearning-samples/tree/master/samples/visualbasic
Since the list of examples will be growing and they will be covering many scenarios depending on ML tasks but also showing typical business problems to solve, the samples are classified by two pivots:
- ML task/area
- Industry/business
The next gallery showcases the same examples but classified by industry/business
Until ML.NET is released as final v1.0, most of the samples in this repo will be using preview released versions (i.e. v0.6, v0.7, etc.) available at NuGet (using released Microsoft.ML NuGet packages). However, a few of the samples might also be using nightly releases available at MyGet using this feed: https://dotnet.myget.org/F/dotnet-core/api/v3/index.json.
In addition, if you would like to explore the examples directly referencing the source code of ML.NET, check out scenario tests in ML.NET repository.
See ML.NET Guide for detailed information on tutorials, ML basics, etc.
Check out the ML.NET API Reference to see the breadth of APIs available.
We welcome contributions! Please review our contribution guide.
Please join our community on Gitter
This project has adopted the code of conduct defined by the Contributor Covenant to clarify expected behavior in our community. For more information, see the .NET Foundation Code of Conduct.
ML.NET Samples are licensed under the MIT license.