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Add cross references to NumPyand SciPy
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docs/scenarios/scientific.rst

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@@ -11,7 +11,8 @@ and it performs really well.
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Due to its high performance nature, scientific computing in python often refers
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to external libraries, typically written in faster languages (like C, or FORTRAN
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for matrix operations). The main libraries used are NumPy and SciPy
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for matrix operations). The main libraries used are `NumPy`_ and
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`SciPy`_.
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Libraries
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