Coinciding with the Microsoft Ignite 2019 conference, we are thrilled to announce the GA release of ML.NET 1.4 and updates to Model Builder in Visual Studio, with exciting new machine learning features that will allow you to innovate your .NET applications.
We are excited today to announce updates to Model Builder and improvements in ML.NET. You can learn more in the “What’s new in ML.NET?.” session at .NET Conf.
ML.NET is an open-source and cross-platform machine learning framework (Windows, Linux, macOS) for .NET developers.
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,
We are excited to announce ML.NET 1.2 and updates to Model Builder and the CLI. ML.NET is an open-source and cross-platform machine learning framework for .NET developers. ML.NET also includes Model Builder (a simple UI tool for Visual Studio) and the ML.NET CLI (Command-line interface) to make it super easy to build custom Machine Learning (ML) models using Automated Machine Learning (AutoML).
This post was written by Lena Hall, a Senior Cloud Developer Advocate at Microsoft.
F# Software Foundation has recently announced their new initiative — Applied F# Challenge! We encourage you to participate and send your submissions about F# on Azure through the participation form.
ML.NET is an open source and cross-platform machine learning framework made for .NET developers. .NET developers can use their C# or F# skills to easily integrate custom machine learning into their web, mobile, desktop, gaming, or IoT applications without any prior expertise in developing or tuning machine learning models.
ML.NET is an open-source and cross-platform framework (Windows, Linux, macOS) which makes machine learning accessible for .NET developers.
ML.NET allows you to create and use machine learning models targeting scenarios to achieve common tasks such as sentiment analysis, issue classification, forecasting,
We’re excited to announce today the release of ML.NET 0.7 – the latest release of the cross-platform and open source machine learning framework for .NET developers (ML.NET 0.1 was released at //Build 2018). This release focuses on enabling better support for recommendation based ML tasks,
This week’s blog post is by Brian Lui, one of our summer interns on the .NET team, who’s been hard at work. Over to Brian:
Hello everyone! This summer I interned in the .NET team, working on ML.NET, an open-source machine learning platform which enables .NET developers to build and use machine learning models in their .NET applications.
Today we’re announcing our latest monthly release: ML.NET 0.6! ML.NET is a cross-platform, open source machine learning framework for .NET developers. We want to enable every .NET developer to train and use machine learning models in their applications and services. If you haven’t tried ML.NET yet,