A little gem of an opening salvo from the "Learning #StandardML", #Tufts U Comp 105 course handout:
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For someone with a background in COMP 11 and COMP 15, the fastest and easiest way to learn Standard ML is to buy Ullman’s book and work through chapters 2, 3, 5, and 6. But many students choose not to buy Ullman—a move that saves money but costs time. You can recover some of the time by reading this guide; it enumerates the most important concepts, and it tells you where to find key information, not just in Ullman, but also in three other sources:
• Jeff Ullman’s "Elements of ML Programming" (ML’97 edition)
• Norman Ramsey’s "Programming Languages: Build, Prove, and Compare"
• Mads Tofte’s “Tips for Computer Scientists on Standard ML" (Revised)
• Bob Harper’s draft "Programming in Standard ML"
Know your sources! Mads Tofte and Bob Harper both worked with Robin Milner on the design of Standard ML, and they helped write the Definition of Standard ML. They know what they’re talking about, and they have good taste—though Tofte’s use of the ML modules is considered idiosyncratic. Norman Ramsey at least knows some functional programming. Jeff Ullman, by contrast, got his start in the theory of formal languages and parsing, then switched to databases. He may like ML, but he doesn’t understand it the way the others do.
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I don't know any professors who teach at Tufts, but the word on the Web is that Ramsey is the author of this handout. Cheeky blighter!
https://www.cs.tufts.edu/comp/105-2017f/readings/ml.pdf