In-Depth

PLEASE REUSE

About the Author

Bill McCarthy is an independent consultant based in Australia and is one of the foremost .NET language experts specializing in Visual Basic. He has been a Microsoft MVP for VB for the last nine years and sat in on internal development reviews with the Visual Basic team for the last five years where he helped to steer the language’s future direction. These days he writes his thoughts about language direction on his blog at http://msmvps.com/bill.

comments powered by Disqus

Featured

  • VS Code v1.99 Is All About Copilot Chat AI, Including Agent Mode

    Agent Mode provides an autonomous editing experience where Copilot plans and executes tasks to fulfill requests. It determines relevant files, applies code changes, suggests terminal commands, and iterates to resolve issues, all while keeping users in control to review and confirm actions.

  • Windows Community Toolkit v8.2 Adds Native AOT Support

    Microsoft shipped Windows Community Toolkit v8.2, an incremental update to the open-source collection of helper functions and other resources designed to simplify the development of Windows applications. The main new feature is support for native ahead-of-time (AOT) compilation.

  • New 'Visual Studio Hub' 1-Stop-Shop for GitHub Copilot Resources, More

    Unsurprisingly, GitHub Copilot resources are front-and-center in Microsoft's new Visual Studio Hub, a one-stop-shop for all things concerning your favorite IDE.

  • Mastering Blazor Authentication and Authorization

    At the Visual Studio Live! @ Microsoft HQ developer conference set for August, Rockford Lhotka will explain the ins and outs of authentication across Blazor Server, WebAssembly, and .NET MAUI Hybrid apps, and show how to use identity and claims to customize application behavior through fine-grained authorization.

  • Linear Support Vector Regression from Scratch Using C# with Evolutionary Training

    Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric value. A linear SVR model uses an unusual error/loss function and cannot be trained using standard simple techniques, and so evolutionary optimization training is used.

Most   Popular

Subscribe on YouTube