The big difference being that I can use ML.NET on macOS, Linux, Windows, with Tensorflow lite on the roadmap. Whereas Swift, pretty much is Apple only.
Even your examples are a proof of that.
Zero persons from Swift/Tensorflow team at Google are working on improving Linux/Windows support.
Linux was been mostly volunteer and some IBM contributions.
Windows are just volunteers, and have restarted the port multiple times.
Well Swift for Tensorflow is more than just a binding to begin with. The difference in maintenance is that Google officially supports Swift whereas Microsoft would be always catching up to keep theirs updated.
> So any language that can target .NET is also able to plug into it, and I certainly would pick F# over Swift.
I can use both Swift for my iOS app (inferencing), training is also possible thanks to Python interoperability (@dynamicCallable), soon to be replaced by native C++ interoperability.
If I chose F#, as much as you may think it is a good choice unless your stack/team is using Microsoft technologies, I see this as a potential sunken cost here and I certainly wouldn't use it for this case and would rather rely on the active maintenance of the Swift/Tensorflow team at Google to improve this rather than using another great language for an unsupported use case.