add link to matplotlib

napari-workshops/home.md

@@ -13,7 +13,7 @@ The slides for the introductory presentation can be accessed [here](https://psob
 
 ## Introducing napari 
 
-Python has a rich selection of [data visualization](https://pyviz.org/index.html) tools that cover a wide range of applications, for example Matplotlib (Hunter, 2007), Mayavi (Ramachandran & Varoquaux, 2011), [ipyvolume](https://github.com/maartenbreddels/ipyvolume/), the yt Project (Turk et al., 2010), [ITK](https://itk.org/) (Johnson, McCormick, Ibanez 2015), and more recently **[napari](http://napari.org)**.
+Python has a rich selection of [data visualization](https://pyviz.org/index.html) tools that cover a wide range of applications, for example [Matplotlib](https://matplotlib.org) (Hunter, 2007), Mayavi (Ramachandran & Varoquaux, 2011), [ipyvolume](https://github.com/maartenbreddels/ipyvolume/), the yt Project (Turk et al., 2010), [ITK](https://itk.org/) (Johnson, McCormick, Ibanez 2015), and more recently **[napari](http://napari.org)**.
 
 For **bioimage visualization** some major challenges are: 
 - working with large and complex images: image size and dimensionality