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README.md

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-# PythonProjectTemplate
+# DoctorsWithoutBorders
 
-This repository presents some opinionated guidelines for creating a data science and machine learning project in Python, using the simple example of scripts for counting words in text documents. By following these guidelines you can make it easy for your code to be tested and understood by others (or yourself months from now), so they can reproduce your experiments.
+Code repository for 2024 Data Science for the Common Good project with Doctors Without Borders.
 
 These are just guidelines, not strict rules, so feel free to alter them to meet your needs. Just keep in mind the goal is that others can understand and run your code, even if you aren't around to ask questions to!
 
@@ -228,4 +228,4 @@ Jupyter notebooks are useful tools for exploratory data analysis, prototyping ba
 
 There _are_ [companies that use notebooks in production architecture](https://blog.goodaudience.com/inside-netflixs-notebook-driven-architecture-aedded32145e), but they have entire Devops organizations to help configure deployment and _still_ use workflow tools like [papermill](https://papermill.readthedocs.io/en/latest/) and Airflow to parametrize notebook dependencies. Unless you are willing to put in the effort to parametrize your notebooks in pipeline workflows, don't use them when stability and reproducibility matter.
 
-Best practices for working with notebooks are changing as they become more popular. However, for now most of these services are too expensive for our partners or difficult to configure. You can use a notebook for prototyping and exploratory analysis, but once the project moves forward, use [`nbconvert`](https://linuxhint.com/convert-jupyter-notebook-python/) to convert the notebook to python code, then add some tests!
+Best practices for working with notebooks are changing as they become more popular. However, for now most of these services are too expensive for our partners or difficult to configure. You can use a notebook for prototyping and exploratory analysis, but once the project moves forward, use [`nbconvert`](https://linuxhint.com/convert-jupyter-notebook-python/) to convert the notebook to python code, then add some tests!