Every project below is real and linked to its source.
Showing 10 projects
End-to-end supply chain analytics covering inventory, warehouse performance, stockouts, backorders, and revenue — SQL cleaning, Excel pivots, Python EDA, and Power BI.
500K+ transactions cleaned in Python and segmented using RFM scoring + K-Means into VIP Champions, High-Value Loyal, Regular, and Lost customers.
120K session dataset analyzed across a 5-stage funnel with SQL analysis, two Power BI dashboard pages, and a Random Forest purchase-prediction Streamlit app.
SQL-driven HR analysis, EDA, Power BI dashboard, and a Streamlit app comparing Logistic Regression against Random Forest with reported feature importance.
Flask app that accepts a CSV, profiles the dataset, detects missing values, duplicates and outliers, computes a health score, and generates a professional PDF report.
Career prediction app (10 IT career categories, ~90% reported accuracy) that generates a Gemini-powered personalized learning roadmap from user inputs.
Random Forest classifier recommends workouts based on age, BMI, fitness goal, and level — with built-in 60-second timers, pause/resume, and sound effects.
End-to-end sales analytics project using SQL, Python, and Power BI. Reported totals include 83.47M sales and 66K+ orders, with demographic and payment analysis.
Classification project on highly imbalanced transactions. Reported Precision 90.90% and Recall 81.63%. Includes SMOTE balancing and SHAP explainability.
Regression-based project estimating delivery time from distance, traffic, and weather features, with a reported R² above 0.85 and a Streamlit app.