A GitHub Action harnessing Azure Cognitive Services Translator to automatically create translation files.
The specification defines many floating point types, including: , , and . Most developers are familiar with (equivalent to in C#) and (equivalent to in C#). They provide a standard format to represent a wide range of values with a precision acceptable for many applications. .NET has always had and and with .NET 5 Preview 7, we've added a ne...
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!
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. ML.NET is an open-source and cross-platform machine learning framework for .NET developers....
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 offers Model Builder Model Builder (a simple UI tool) and CLI to m...
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, and since then the te...
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) mo...
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 encourage in-dept...
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 machin...
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, recommendations, fraud detection, ima...
