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I'm just guessing, but:

1. Open Source.

2. Easy to learn. (kind of)

3. Robust plotting and visualization capabilities, which are integral (I f*cking swear no pun intended) to understanding calculus, the foundational purpose of calculus being to find the area under the curve. (something I really wish they told me day one of Pre-Calc)

4. This one is just a vague feeling, but the fact that Python's most robust Symbolic Regression package, SymPy, relies on running Julia in the background to do all the real work suggests to me that Julia is somehow just superior when it comes to formulas as opposed to just calculations. IDK how, though.



1-3 apply exactly the same to python, 4 is just false, SymPy is written in python, it has nothing to do with Julia.


They're thinking of PySR but you are right on all points!




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