Eventually I would learn Ocaml, as it's the more sensible language for most production code (community, tooling, ecosystem, etc.). But there's nothing wrong wit

Eventually I would learn Ocaml, as it's the more sensible language for most production code (community, tooling, ecosystem, etc.). But there's nothing wrong with learning SML first. 90% of what you learn will be transferable to Ocaml. Starting with SML might help you focus on the "essence" of ML languages rather than getting overwhelmed by the impressive range of options that Ocaml opens up. The MLton implementation of SML -- while not necessarily the best ML to practice on -- is particularly interesting because it's a whole-program optimizing compiler. It has a reputation for producing very compact, efficient machine code. Having said that, Ocaml is still a comparatively simple language -- compared to say, Haskell or C++ -- and its native compiler is well known for turning out decent and very predictable code (predictable in the sense that you can read some source code and have a decent understanding of what kind of machine code it will get compiled into). If you decide to learn Ocaml first, but want to stick to "essential ML", I would recommend Jason Hickey's "Introduction to Ocaml" [1] over the more modern "Real World Ocaml" [2], as the latter book introduces every bell and whistle that Ocaml offers, and has a much more ecosystem-dependent focus (third party libraries, third party tooling, etc.). Still a fine book, but I think it emphasizes advanced Ocaml features a bit too much for an introductory text. [1] http://courses.cms.caltech.edu/cs134/cs134b/book.pdf http://courses.cms.caltech.edu/cs134/cs134b/book.pdf [2] https://realworldocaml.org/ https://realworldocaml.org/