Use note directive.

Author: rossbar

content/tutorial-svd.md

@@ -43,7 +43,18 @@ from scipy.datasets import face
 img = face()
 ```
 
-**Note**: If you prefer, you can use your own image as you work through this tutorial. In order to transform your image into a NumPy array that can be manipulated, you can use the `imread` function from the [matplotlib.pyplot](https://matplotlib.org/api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot) submodule. Alternatively, you can use the [imageio.imread](https://imageio.readthedocs.io/en/stable/_autosummary/imageio.v3.imread.html) function from the `imageio` library. Be aware that if you use your own image, you'll likely need to adapt the steps below. For more information on how images are treated when converted to NumPy arrays, see [A crash course on NumPy for images](https://scikit-image.org/docs/stable/user_guide/numpy_images.html) from the `scikit-image` documentation.
+```{note}
+If you prefer, you can use your own image as you work through this tutorial.
+In order to transform your image into a NumPy array that can be manipulated, you
+can use the `imread` function from the
+[matplotlib.pyplot](https://matplotlib.org/api/_as_gen/matplotlib.pyplot.html#module-matplotlib.pyplot) submodule.
+Alternatively, you can use the
+[imageio.imread](https://imageio.readthedocs.io/en/stable/_autosummary/imageio.v3.imread.html)
+function from the `imageio` library.
+Be aware that if you use your own image, you'll likely need to adapt the steps below.
+For more information on how images are treated when converted to NumPy arrays,
+see [A crash course on NumPy for images](https://scikit-image.org/docs/stable/user_guide/numpy_images.html) from the `scikit-image` documentation.
+```
 
 +++