I'd second mint for anyone who wants a "it just werks (TM)" experience with minimal configuration to throw on anything except a server.
For servers, these days I'd recommend Alpine on ARM architecture for a very good mix of high performance and having sane defaults set up so you can easily set up a reverse proxy, web server, etc.
OpenSUSE is nice. It has btrfs/snapper configured by default, which makes upgrades low-stress (if anything ever goes wrong, just reboot into the snapshot automatically created before every upgrade.) It also has a decent GUI (YaST) for system administration tasks.
I love OpenSUSE (esp. Tumbleweed), but every time I see a tutorial about ML stuff, they are using Ubuntu. I wonder if there's any inherent advantage to Ubuntu that other distros don't have (e.g., having some libraries preinstalled, sane default configs, etc.)
> I wonder if there's any inherent advantage to Ubuntu
No advantage, but Ubuntu is the most popular distro for regular users / tutorial customers. Ubuntu also has the widest availability of support resources, even though the information is often not Ubuntu-specific.
If you use a non-Ubuntu (or non-Debian-derived) distro, you'll need to do a little bit of package-name mapping to get the prerequisites installed. This is annoying but only has to be done once (take notes!).
The bigger problem I've had with ML libs is that they're very picky about version compatibilities. Once you settle on a set of working/compatible versions (libs, python, python pkgs), make some effort to preserve your sources. Package versions can get deleted from the official repos, be prepared to build from source, etc.
