The problem
A lot of countries have implemented a variety of policies to tackle the COVID-19 pandemic and all of them have seen different results to the policies put in place. Depending on location, population, and a variety of different factors different measures have been put in place. Most of the countries implemented lockdowns around the world but some were more successful than others. Vaccine distribution has been done in very different ways.
Our goal would be to analyze all policies and build an NLP-based solution for recommending ideas on how to distribute vaccines and how to better tackle a potential third wave or avoid future pandemics.
The project results will be made open source. The aim is for the model to potentially be used by government agencies to improve governance using AI and reduce any further casualties. The model can be further repurposed to support and build effective policies for any natural calamity in the near future.
Goal of the project
- Analyse COVID policies around the world.
- Figure out the most important features of policies from each country.
- Perform topic modeling on the policies.
- Build a recommendation system for best policies around the world.
- AI suggests customized policies specific to a region/demographic.
What you'll learn
1. Systematic research on COVID policies around the world.
2. Data collection using web scraping, API calls, and flat files .
3. Creating a Relational Database on a Cloud platform.
4. Data Analysis on both structured and unstructured data.
5. Feature identification specific to a country.
6. Topic modeling (NLP) on the policies.
7. Build a recommendation system that suggests policies specific to a region/demographic.