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Use note directive.
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content/tutorial-svd.md

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@@ -155,7 +155,19 @@ It is possible to use methods from linear algebra to approximate an existing set
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**Note**: We will use NumPy's linear algebra module, [numpy.linalg](https://numpy.org/devdocs/reference/routines.linalg.html#module-numpy.linalg), to perform the operations in this tutorial. Most of the linear algebra functions in this module can also be found in [scipy.linalg](https://docs.scipy.org/doc/scipy/reference/linalg.html#module-scipy.linalg), and users are encouraged to use the [scipy](https://docs.scipy.org/doc/scipy/reference/index.html#module-scipy) module for real-world applications. However, some functions in the [scipy.linalg](https://docs.scipy.org/doc/scipy/reference/linalg.html#module-scipy.linalg) module, such as the SVD function, only support 2D arrays. For more information on this, check the [scipy.linalg page](https://docs.scipy.org/doc/scipy/tutorial/linalg.html).
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```{note}
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We will use NumPy's linear algebra module,
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[numpy.linalg](https://numpy.org/devdocs/reference/routines.linalg.html#module-numpy.linalg),
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to perform the operations in this tutorial.
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Most of the linear algebra functions in this module can also be found in
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[scipy.linalg](https://docs.scipy.org/doc/scipy/reference/linalg.html#module-scipy.linalg),
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and users are encouraged to use the [scipy](https://docs.scipy.org/doc/scipy/reference/index.html#module-scipy)
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module for real-world applications.
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However, some functions in the
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[scipy.linalg](https://docs.scipy.org/doc/scipy/reference/linalg.html#module-scipy.linalg)
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module, such as the SVD function, only support 2D arrays.
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For more information on this, check the [scipy.linalg page](https://docs.scipy.org/doc/scipy/tutorial/linalg.html).
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```
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