Hamza Salah
Data Science M.S. candidate passionate about analyzing data, building predictive models, and applying machine learning to real-world problems.
Time Series Analysis of US Retail Sales
Project Overview
This academic project applies time series forecasting to historical US retail sales data (1992–2021), highlighting the impacts of COVID-19 on trends and recovery patterns.
Key Insights
- ARIMA model captured post-2020 recovery trends.
- Seasonal patterns showed predictable holiday spikes.
- RMSE indicates reliable short-term predictions for retail planning.