Not that many options I think. A classic is Larry C Paulson's "ML for the Working Programmer", although it's (a) apparently a bit divisive (see e.g. https://ne

Not that many options I think. A classic is Larry C Paulson's "ML for the Working Programmer", although it's (a) apparently a bit divisive (see e.g. https://news.ycombinator.com/item?id=9667264 https://news.ycombinator.com/item?id=9667264) and (b) out of print. It's a thoughtful treatment of functional programming that happens to use ML, and a book I enjoy reading rather than just referring to. I appreciate the fact that the second edition introduces modules very early on, and that it's relatively un-mathematical in the way it presents things like module semantics. Robert Harper's "Programming in Standard ML" (online only I think, at http://www.cs.cmu.edu/~rwh/smlbook/book.pdf http://www.cs.cmu.edu/~rwh/smlbook/book.pdf) is more thorough. It's modern enough to present the Basis library as part of the language, so you do get a handful of useful existing data structures rather than feeling you're expected to build everything yourself. A pity the Basis library is so slight though.