We’re excited to announce general availability of F# 4.6 and the F# tools for Visual Studio 2019! In this post, I’ll show you how to get started, explain the F# 4.6 feature set, give you an update on the F# tools for Visual Studio,
Over the last couple of years, we worked with experts to create some incredible architecture guides & reference samples for .NET developers. We focused on Microservices Architecture, Modernizing existing .NET apps, DevOps best practices, ASP.NET web apps, Azure cloud apps, Mobile apps with Xamarin and more.
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.
When you are debugging an application, there are many tools and techniques you can use, like logs, memory dumps and Event Tracing for Windows (ETW). In this post, we will talk about Time Travel Debugging, a tool used by Microsoft Support and product teams and more advanced users,
F# 4.6 is now fully released. See the announcement blog post for more.
We’re excited to announce that Visual Studio 2019 will ship a new version of F# when it releases: F# 4.6!
F# 4.6 is a smaller update to the F# language,
Windows Desktop applications are coming to .NET Core. The recently released .NET Core 3.0 Preview 1 version includes WinForms and WPF support.
To make .NET Core 3.0 viable for as many of you as possible, we have created a survey to understand the types of desktop applications you want to build with .NET Core.
The Security and Quality Rollup is available via Windows Update, Windows Server Update Services, and Microsoft Update Catalog.
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 models.
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.
We have another early access build to share today! This release includes several accessibility, performance, reliability and stability fixes across the major framework libraries. We will continue to stabilize this release and take more fixes over the coming months and we would greatly appreciate it if you could help us ensure Build 3707 is a high-quality release by trying it out and providing feedback on the new features via the .NET Framework Early Access GitHub repository.