Discover how C# developers can build a complete house price prediction system using ML.NET. Learn data generation, model training, and production deployment with familiar C# patterns.

Transform from a coder into an AI architect. This guide demystifies generative AI, teaching you when to use conversational "Vibe Coding" versus structured "Spec Coding." Master prompt engineering to write better, more secure code and avoid common AI pitfalls.

Is migrating from.NET Framework to .NET 8+ worth it? Explore the huge performance gains, security benefits, and cross-platform capabilities. Discover how new AI tools and features make the upgrade more compelling and easier than ever.

Ready to build AI-powered apps? Discover how .NET developers can create powerful generative AI solutions using C#, ML.NET, and Semantic Kernel. Learn to leverage existing skills to build enterprise-grade chatbots, content generators, and more - Python not required.

I explored Google Gemini and was impressed by its speed compared to ChatGPT! My hands-on experience, from coding .NET regex to using the free API tier in Google AI Studio, is detailed in this article. Even though Gemini's Semantic Kernel integration is new, I easily adapted an OpenAI example. If you're curious about a powerful OpenAI alternative, especially within the Google ecosystem, you need to read this.

Recently, I explored using Semantic Kernel and OpenAI for more accurate page scanning. By converting HTML to markdown and extracting metatags with XPath, I reduced input size and improved efficiency. OpenAI’s new JSON output feature further allowed me to receive structured data, making the process more reliable.

I was recently working on learning more about using Dataframes and Polyglot Notebooks with C# and needed some sample data to work with. At first I started by looking for some examples online, but I wanted to write a blog about my experience and wanted my own sample of data.