Discovering Disease Outbreaks from News Headlines

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prerequisites
intermediate Python • beginner scikit-learn • basics of pandas • basics of data science
skills learned
text extraction with pandas • clustering with K-means and DBSCAN • visualize clusters
Leonard Apeltsin and Will Koehrsen
4 weeks · 5-10 hours per week · INTERMEDIATE

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Look inside
In this liveProject, you’ll take on the role of a data scientist at the World Health Organization (WHO). The WHO is responsible for responding to international epidemics, a critical component of which involves monitoring global news headlines for signs of disease outbreaks. However, this daily deluge of news data is too huge to manually analyze. Your challenge is to pull geographic information from headlines, and determine where in the world outbreaks are occurring. Problems you will have to solve include extracting information from text using regular expressions, using the Basemap Matplotlib extension to visualize map locations for patterns indicating an epidemic, and reporting your findings to your superiors so resources can be dispatched.
This project is a part of the series Data Science Bookcamp Projects.
This project is designed for learning purposes and is not a complete, production-ready application or solution.

prerequisites

The liveProject is for intermediate Python programmers who know the basics of data science. To begin this liveProject, you will need to be familiar with:

TOOLS
  • Basics of pandas
  • Basics of scikit-learn
  • Basics of text extraction
  • Basics of K-means and DBSCAN clustering
  • Basics of Jupyter Notebook

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