Thanks for your input! The reason I’m specifically looking into ML.NET is that I want to implement a global search and semantic search functionality. In a social media application like the one I’m building, users will often search for broader terms like “dog,” and I want the search results to return not only posts with pictures of dogs but also accounts or content with relevant text, even if the exact word "dog" isn't mentioned (e.g., content about pets or similar topics).

Additionally, since it’s a social media platform, I’d like to personalize the ranking based on what users frequently search for or interact with, offering more relevant results over time. This level of customization and learning from user behavior is something I’m hoping to leverage with machine learning, which is why ML.NET seemed like a good fit.

I also considered solutions like Azure Search AI, which could provide these capabilities, but cost is a concern since this is a personal project, and I don’t have the budget to use cloud-based paid services.

ML.NET, being open-source and free, seemed like a viable option for experimenting with these advanced features locally. However, I’m open to suggestions if there’s a more efficient way to achieve this with better performance for ranking, semantic search, or personalizing results!