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| author | Melissa Weber Mendonça <melissawm@gmail.com> | 2020-01-24 10:42:35 -0300 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2020-01-24 10:42:35 -0300 |
| commit | c53bd9b4eb0577e7e560cb5c20b4267ab77ffac5 (patch) | |
| tree | 96ba44ad8edc9043dbde76d720e9ae9a79005548 | |
| parent | a7bd2529a6a6a01d54d91db6934675cf1b7f2185 (diff) | |
| download | numpy-c53bd9b4eb0577e7e560cb5c20b4267ab77ffac5.tar.gz | |
Update doc/source/user/tutorial-svd.rst
Co-Authored-By: Anne Bonner <35413198+bonn0062@users.noreply.github.com>
| -rw-r--r-- | doc/source/user/tutorial-svd.rst | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/source/user/tutorial-svd.rst b/doc/source/user/tutorial-svd.rst index 466538db5..f77064617 100644 --- a/doc/source/user/tutorial-svd.rst +++ b/doc/source/user/tutorial-svd.rst @@ -299,7 +299,7 @@ use **Applying to all colors** -Now, we want to do the same kind of operation, but to all three colors. Our +Now we want to do the same kind of operation, but to all three colors. Our first instinct might be to repeat the same operation we did above to each color matrix individually. However, NumPy's `broadcasting <https://numpy.org/devdocs/user/basics.broadcasting.html>`_ takes care of this for us. |