.NET Blog

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Submit to the Applied F# Challenge!

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. Applied F# Challenge is a new initiative to ...

Announcing ML.NET 0.9 – Machine Learning for .NET

  Announcing ML.NET 0.9 - Machine Learning for .NET (image) 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 ...

Tell us your thoughts on ML.NET, an open source and cross-platform machine learning framework

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 covers many ...

Announcing ML.NET 0.7 (Machine Learning .NET)

(image) 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, enabling anomaly detection, enhancing the ...

Using .NET Hardware Intrinsics API to accelerate machine learning scenarios

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. ...

Announcing ML.NET 0.6 (Machine Learning .NET)

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, here’s how you can get started! The ...

Introducing Tensor for multi-dimensional Machine Learning and AI data

Overview 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.  Tensor<T> is ...

Why you should use F#

Why you should use F# This post was written by Phillip Carter and Mads Torgersen. Both work on languages on the .NET team. At Build 2017, we presented a tech talk entitled "Why You Should Use F#". However, not everyone can attend Build, and many attendees were unable to find a position in the room where they could adequately hear us. You ...