Hey, I guess OP here. These are part of the workshop notes from 2017 (with a few updates, but mostly left intact) on "A Deep Introduction to Julia for Data Scie

Hey, I guess OP here. These are part of the workshop notes from 2017 (with a few updates, but mostly left intact) on "A Deep Introduction to Julia for Data Science and Scientific Computing". It's a full day 8am-3pm workshop (with extended problem exercises to take home!) that can be found here: http://ucidatascienceinitiative.github.io/IntroToJulia/ http://ucidatascienceinitiative.github.io/IntroToJulia/ The section that was pulled out to be the heading link here was the portion that comes after first explaining the semantics of the language. The "Why Julia?" section is an explanation of why Julia is fast but also the engineering trade-offs that were made to get it done (and thus the drawbacks of the approach). That is the page is that is linked, but if you're curious about the greater context of this page (and learning the language) do check out the rest of the notes. I will say that they are a bit old (one comment noted that a compiler specializations on literals does handle one of the cases I pointed out in the trade-offs) but for the most part are still a good introduction to the Julia programming language. Surprising to have people tell me this ended up on Hacker News but exciting to see!