Showing results for Machine Learning - .NET Blog

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. The ML.N...

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 ML.NET 0.6 ...

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 designed t...

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 can se...