Taiwan Air Quality Analysis & Prediction Project (AQI Analysis & ML Modeling)

An end-to-end data science project analyzing time-series environmental data and predicting the Air Quality Index (AQI) in Taiwan (2016–2024) following the CRISP-DM methodology.

Key Highlights:

Data Processing: Cleaned and structured a large-scale dataset of 5.8M+ records

.Exploratory Analysis: Identified $PM_{10}$ and $O_3$ as the primary drivers behind 68%+ of air pollution.

Machine Learning: Evaluated models (Linear Regression vs. Decision Tree), achieving an $R^2$ score of 0.994 with Decision Tree.

Interactive Dashboard: Built a Streamlit web app for real-time AQI prediction and interactive data visualization.