Clustering Life Expectancy
Data Science & Analyst
About The Project
This project performs exploration and clustering of life expectancy data from various countries using the DBSCAN algorithm (Density-Based Spatial Clustering of Applications with Noise). The main objective is to identify hidden patterns and group countries with similar health characteristics based on life expectancy indicators.
Tools & Libraries : Python, Google Colab, Pandas, Numpy, Seaborn, Matplotlib, Scikit-Learn, Kneed.
Achievements
This project successfully clustered countries based on the average life expectancy of males, females, and both sexes using the DBSCAN algorithm to uncover patterns and outliers among nations.
Links
azzriala@gmail.com
+6287872788220
