Check out what's new in ML.NET and Model Builder.

Check out what's new in ML.NET and Model Builder.

Take the ML.NET survey to let us know what you want to see next for Machine Learning in .NET.

This release of ML.NET and Model Builder brings numerous bug fixes and enhancements as well as new features, including config-based training and a redesigned Consume step.

This release of ML.NET Model Builder brings numerous bug fixes and enhancements as well as new features, including advanced data loading options and streaming training data from SQL.

Machine Learning Operations (MLOps) is like DevOps for the machine learning lifecycle. This includes things like model deployment & management and data tracking, which help with productionizing machine learning models. Through the survey below, we'd love to get feedback on your current DevOps practices as well as your prospective usage of ML...

This release of ML.NET (1.5.2) brings numerous bug fixes and enhancements, while tooling updates include the ability to train object detection models using Azure ML via Model Builder and to locally train image classification models with the ML.NET CLI.

ML.NET is an open-source, cross-platform machine learning framework for .NET developers. It enables integrating machine learning into your .NET apps without requiring you to leave the .NET ecosystem or even have a background in ML or data science. ML.NET provides tooling (Model Builder UI in Visual Studio and the cross platform ML.NET CLI) that aut...

ML.NET is a cross-platform, machine learning framework for .NET developers. Model Builder is the UI tooling in Visual Studio that uses Automated Machine Learning (AutoML) to train and consume custom ML.NET models in your .NET apps. You can use ML.NET and Model Builder to create custom machine learning models without having prior machine learning ex...

ML.NET is an open source and cross-platform machine learning framework made for .NET developers. Using ML.NET, you can stay in .NET to easily build and consume custom machine learning models for scenarios like sentiment analysis, price prediction, sales forecasting, recommendation, image classification, and more. Over the past six months, the tea...