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authorMelissa Weber Mendonça <melissawm@gmail.com>2020-01-24 10:45:02 -0300
committerGitHub <noreply@github.com>2020-01-24 10:45:02 -0300
commit92f35eae75e978c87a4fd37476f3e9aca07e9523 (patch)
treee38d0ae190de311fb6d3fb6ea229c8999e7c1e65 /doc
parent3cc5a249afc39b703955077864a6e42421ddb098 (diff)
downloadnumpy-92f35eae75e978c87a4fd37476f3e9aca07e9523.tar.gz
Update doc/source/user/tutorial-svd.rst
Co-Authored-By: Anne Bonner <35413198+bonn0062@users.noreply.github.com>
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diff --git a/doc/source/user/tutorial-svd.rst b/doc/source/user/tutorial-svd.rst
index 6e21c38e9..aadcfb542 100644
--- a/doc/source/user/tutorial-svd.rst
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@@ -424,7 +424,7 @@ distinguishing features from this image.
**Final words**
Of course, this is not the best method to *approximate* an image.
-However, there is in fact a result in linear algebra that says that the
+However, there is, in fact, a result in linear algebra that says that the
approximation we built above is the best we can get to the original matrix in
terms of the norm of the difference. For more information, see *G. H. Golub and
C. F. Van Loan, Matrix Computations, Baltimore, MD, Johns Hopkins University