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Mention Julia package in README

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- # [PySR.jl](https://github.com/MilesCranmer/PySR)
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  (pronounced like *py* as in python, and then *sur* as in surface)
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@@ -13,6 +13,9 @@ Uses regularized evolution, simulated annealing, and gradient-free optimization.
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  [Documentation](https://pysr.readthedocs.io/en/latest)
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  Symbolic regression is a very interpretable machine learning algorithm
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  for low-dimensional problems: these tools search equation space
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  to find algebraic relations that approximate a dataset.
 
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+ # [PySR](https://github.com/MilesCranmer/PySR)
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  (pronounced like *py* as in python, and then *sur* as in surface)
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  [Documentation](https://pysr.readthedocs.io/en/latest)
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+ Check out [SymbolicRegression.jl](https://github.com/MilesCranmer/SymbolicRegression.jl) for
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+ the pure-Julia version of this package.
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  Symbolic regression is a very interpretable machine learning algorithm
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  for low-dimensional problems: these tools search equation space
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  to find algebraic relations that approximate a dataset.