ML.NET is a machine learning framework built for .NET developers.
Use your .NET and C# or F# skills to easily integrate custom machine learning into your applications without any prior expertise in developing or tuning machine learning models.
ML.NET is open source and runs on Windows, Linux, and macOS.
Our public release is still in-development, and we want your help! Join the community and contribute your ideas to help us shape what comes next.
Use the same framework behind recognized Microsoft features like Windows Hello, Bing Ads, and PowerPoint Design Ideas to power your own applications.
We're building ML.NET as an extensible framework, with support for Light GBM, Accord.NET, CNTK, and TensorFlow coming soon.
Add machine learning to your existing .NET apps. ML.NET supports popular machine learning scenarios like sentiment analysis, forecasting, recommendation, and more. ML.NET also supports deep learning scenarios like image classification with TensorFlow. Probabilistic programming is supported through Infer.NET, which extends ML.NET with capabilities for bayesian analysis and online learning.
Learn the basics of machine learning and how to develop and integrate custom machine learning models into your applications using ML.NET.
1hr 5min duration
In this book we look at machine learning from a fresh perspective which we call model-based machine learning. Model-based machine learning makes the process of creating effective machine learning solutions much more transparent.