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Free. Cross-platform. Open source. A developer platform for building all your apps.
August 21, 2019Aug 21, 201908/21/19ML.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,
July 17, 2019Jul 17, 201907/17/19We 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).
February 5, 2019Feb 5, 201902/5/19This 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.
![Bri Achtman [MSFT]](https://devblogs.microsoft.com/dotnet/wp-content/uploads/sites/10/2019/02/BriAchtman.jpeg){kind=avatar}
January 9, 2019Jan 9, 201901/9/19ML.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.
December 4, 2018Dec 4, 201812/4/18ML.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,
November 8, 2018Nov 8, 201811/8/18We’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,
October 10, 2018Oct 10, 201810/10/18This 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.
October 8, 2018Oct 8, 201810/8/18Today 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,
November 15, 2017Nov 15, 201711/15/17Overview
Tensor is an exchange type for homogenous multi-dimensional data for 1 to N dimensions. The motivation behind introducing Tensor<T> is to make it easy for Machine Learning library vendors like CNTK, Tensorflow, Caffe, Scikit-Learn to port their libraries over to .NET with minimal dependencies in place.
