Machine Learning · 2026
Covid 19 global Analysis
An exploratory analysis of global COVID-19 data, examining patterns in confirmed cases, deaths, recoveries, and trends across countries and regions. Used data cleaning, aggregation, and visualization to uncover how the pandemic evolved over time and highlight differences in its impact across locations.
- Role
- End-to-end-build
- Year
- 2026
- Type
- Machine Learning
The question
An exploratory analysis of global COVID-19 data, examining patterns in confirmed cases, deaths, recoveries, and trends across countries and regions. Used data cleaning, aggregation, and visualization to uncover how the pandemic evolved over time and highlight differences in its impact across locations.
Approach
Built end-to-end in a Jupyter notebook: data cleaning and inspection first, then feature preparation, then the smallest model that could answer the question honestly. The full walkthrough, code, and figures live on GitHub.
Stack
- python
- pandas
- matplotlib
- seaborn
- Numpy