Bri Achtman

ML.NET Model Builder is now a part of Visual Studio

May 19th, 2020

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 learn

What do you want to see next in ML.NET?

March 11th, 2020

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, th

February ML.NET Model Builder Updates

March 2nd, 2020

With the ML.NET Model Builder, create custom machine learning models for scenarios like sentiment analysis, price prediction, and more without any machine learning experience and without leaving the .NET ecosystem!

ML.NET Model Builder Updates

November 12th, 2019

ML.NET is a cross-platform, machine learning framework for .NET developers, and Model Builder is the UI tooling in Visual Studio that uses Automated Machine Learning (AutoML) to easily allow you to train and consume custom ML.NET models.

Hey .NET! Have you tried ML.NET?

August 21st, 2019

ML.NET is an open source and cross-platform machine learning framework made for .NET developers. Using ML.NET you can easily build custom machine learning models for scenarios like sentiment analysis, price prediction, sales forecasting, recommendation, image classification, and more. ML.NET 1.0 was released at //Build 2019, and since then

Announcing ML.NET 0.11 – Machine Learning for .NET

March 8th, 2019

ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS) for .NET developers. Using ML.NET, developers can leverage their existing tools and skillsets to develop and infuse custom AI into their applications by creating custom machine learning models for common scenarios like Sentiment Analysis, Recommendat