Update portal/cookbook-guide.md

BR suggested change 1

Co-authored-by: Brian Rose <brose@albany.edu>

Author: ktyle

portal/cookbook-guide.md

@@ -35,7 +35,7 @@ Cookbooks can most often succeed by relying on data that are publicly accessible
 1. **Remotely access open data**<br>For most Cookbooks that rely on data to demonstrate their concepts, we recommend accessing open, public datasets remotely in a sustainable way. Use tools like [Xarray](https://xarray.dev), [Siphon](https://www.unidata.ucar.edu/software/siphon), and [Intake](https://intake.readthedocs.io) to read data from providers such as [NOAA NCEI](https://www.ncei.noaa.gov), [AWS Open Data](https://registry.opendata.aws), [Google Cloud Public Datasets](https://cloud.google.com/datasets) and [Source Cooperative](https://source.coop), as long as such data are licensed and priced openly for public demonstration and use. Examples of existing Cookbooks that follow this preferred method include the [CMIP6 Cookbook](https://projectpythia.org/cmip6-cookbook/) and the [CESM LENS on AWS Cookbook](https://projectpythia.org/cesm-lens-aws-cookbook/).
 
 2. **Commit a small data artifact to your Cookbook repository**
-If a few data files whose total size amount to less than 50MB can power your Cookbook, these can be directly stored in your `git` repository! *Make sure you have the license to provide such datasets*. An example Cookbook is the [Landsat ML Cookbook](https://projectpythia.org/landsat-ml-cookbook/README.html). *Note that the more files you commit and the larger they are, the more sluggish your Cookbook's notebooks will quickly become*. Exercise restraint!
+If a few data files whose total size amount to less than 50MB can power your Cookbook, these can be directly stored in your `git` repository! *Make sure you have the license to provide such datasets*. An example Cookbook is the [Landsat ML Cookbook](https://projectpythia.org/landsat-ml-cookbook/). *Note that the more files you commit and the larger they are, the more sluggish your Cookbook's notebooks will quickly become*. Exercise restraint!
 
 3. **Generate “toy” sample data in your Cookbook**
 For many concepts, we encourage writing self-contained functions to generate simple representative datasets for demonstrating scientific concepts. Your Cookbook can even reuse these sample data repeatedly throughout.