Hi all,

I wanted to share a new PyData Seattle talk that may interest SymPy users. The 
talk explores a broad question: Which equations have closed-form solutions, and 
which never will?

To investigate this, I cheated. Instead of using advanced algebra, Galois 
theory, or transcendental number theory, I used Python and SymPy to probe 
families of equations:

  *   polynomials (including degree ≥5),
  *   equations mixing x with exp/log (Lambert W appears),
  *   trigonometric equations with commensurate and non-commensurate 
frequencies,
  *   and mixed combinations of trig, exp, and log.


The talk shows when SymPy succeeds symbolically, when it falls back to 
numerical methods, and when equations seem fundamentally unsolvable in closed 
form.
New Video: https://www.youtube.com/watch?v=02Bchtfb0AI
Free article: 
https://medium.com/data-science/explore-solvable-and-unsolvable-equations-with-python-661ac11f4f20

Thanks to everyone who contributes to SymPy. It's an excellent tool for 
exploring these questions.

Best,
Carl Kadie

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