Merge pull request jakevdp#40 from fuglede/patch-2

Fix a small typo

Author: jakevdp

notebooks/03.12-Performance-Eval-and-Query.md

@@ -69,7 +69,7 @@ mask = tmp1 & tmp2
 
 In other words, *every intermediate step is explicitly allocated in memory*. If the ``x`` and ``y`` arrays are very large, this can lead to significant memory and computational overhead.
 The Numexpr library gives you the ability to compute this type of compound expression element by element, without the need to allocate full intermediate arrays.
-The [Numexpr documentation](https://github.com/pydata/numexpr) has more details, but for the time being it is sufficient to say that the library accepts a *string* giving the NumPy-style expression you'd like to comute:
+The [Numexpr documentation](https://github.com/pydata/numexpr) has more details, but for the time being it is sufficient to say that the library accepts a *string* giving the NumPy-style expression you'd like to compute:
 
 ```python
 import numexpr