CS465 - Machine Learning · Prince Sultan University
Author: Nouf Almojel
A machine learning analysis of real Saudi retail sales data from Tamimi Supermarkets — one of Saudi Arabia's largest supermarket chains. The goal was to uncover purchasing patterns, identify top-performing product categories, and apply ML models to derive actionable business insights.
- Identified the top-performing product categories by sales volume and revenue
- Uncovered seasonal and time-based purchasing trends across store regions
- Applied classification and regression models to predict sales behaviour
- Visualised customer purchasing patterns using heatmaps and distribution plots
| Tool | Purpose |
|---|---|
| Python | Core analysis language |
| Pandas | Data cleaning & manipulation |
| Scikit-learn | Machine learning models |
| Matplotlib / Seaborn | Data visualisation |
| Jupyter Notebook | Development environment |