ML.NET Archives | .NET Blog

Introducing the Half type!

Prashanth GovindarajanAugust 31, 2020Aug 31, 202008/31/20

The IEEE 754 specification defines many floating point types, including: binary16, binary32, binary64 and binary128. Most developers are familiar with binary32 (equivalent to float in C#) and binary64 (equivalent to double in C#). They provide a standard format to represent a wide range of values with a precision acceptable for many ...

August ML.NET API and Tooling Updates

Bri AchtmanAugust 20, 2020Aug 20, 202008/20/20

ML.NET is an open-source, cross-platform machine learning framework for .NET developers. It enables integrating machine learning into your .NET apps without requiring you to leave the .NET ecosystem or even have a background in ML or data science. ML.NET provides tooling (Model Builder UI in Visual Studio and the cross platform ML.NET CLI) ...

Using ML.NET for deep learning on images in Azure

Luis QuintanillaMay 6, 2020May 6, 202005/6/20

This post will show you how to train a custom image classification model in Azure to categorize flowers using ML.NET Model Builder. Then, you can leverage your existing .NET skills to consume the trained model inside a C# .NET Core console application. Best of all, little to no prior machine learning knowledge is required.

February ML.NET Model Builder Updates

Bri AchtmanMarch 2, 2020Mar 2, 202003/2/20

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

Bri AchtmanNovember 12, 2019Nov 12, 201911/12/19

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.

Announcing ML.NET 1.0

Ankit AsthanaMay 6, 2019May 6, 201905/6/19

We are excited to announce the release of ML.NET 1.0 today. ML.NET is a free, cross-platform and open source machine learning framework designed to bring the power of machine learning (ML) into .NET applications. https://github.com/dotnet/machinelearning Star Get Started @ http://dot.net/ml ML.NET allows you to train, build ...

Announcing ML.NET 0.9 – Machine Learning for .NET

Cesar De la TorreJanuary 10, 2019Jan 10, 201901/10/19

Announcing ML.NET 0.9 - Machine Learning for .NET 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...

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

Bri AchtmanJanuary 9, 2019Jan 9, 201901/9/19

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)

Cesar De la TorreNovember 8, 2018Nov 8, 201811/8/18

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 ...

Announcing ML.NET 0.6 (Machine Learning .NET)

Cesar De la TorreOctober 8, 2018Oct 8, 201810/8/18

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 ...

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