Predict the profitability of potential coffee shop locations using SQL and Python. Combines data engineering with feature-rich regression modeling, visual analytics, and business insights to support data-driven site selection and retail decision-making.

Python project for Market Basket Analysis. Generates synthetic retail transactions, mines frequent itemsets using Apriori & FP-Growth, derives association rules, and outputs CSVs + visualizations. Portfolio-ready example demonstrating data science methods for uncovering product co-purchase patterns.

A complete exploratory data analysis (EDA) and forecasting project focused on retail sales data. The project identifies key sales patterns, seasonal trends, and builds predictive models to forecast future demand at the item-store level.

Analyze retail sales data using SQL and Python. Build a SQLite database from CSV, run SQL queries for key KPIs (revenue, top products, AOV, trends), and visualize results with Matplotlib. A portfolio-ready project demonstrating SQL + data analytics + reporting automation.

A powerful eBay scraper built with Scrapy that extracts product listings, prices, seller data, and auction information from eBay marketplaces worldwide. Features anti-bot protection, price intelligence, multi-format export (CSV/JSON), and global eBay site support.

A real-time Retail Shelf Monitoring System using computer vision and machine learning. Detects out-of-stock products, misplaced items, and ensures planogram compliance through intelligent video analytics and a desktop management interface.

MobileNetV2-UNet semantic segmentation for Starbucks logo detection - 50ms inference with PyTorch Lightning, binary mask output for mobile deployment

A real-time bidirectional people counting and foot-traffic analytics system powered by YOLOv11 and OpenCV. Features multi-object tracking (MOT), dual-polygon region-of-interest (ROI) logic for entry/exit detection, and automated video reporting. Perfect for retail analytics and smart occupancy monitoring.

A synthetic digital twin of a retail supply chain network, simulating the optimization model annual refresh process used by large retailers (Home Depot, Walmart, Lowe’s, Amazon) to guide long-range supply chain investments and explore cost, service and scenario tradeoffs. [Website is frontend only, DB is stored locally in SQLite]

Retail-RAG: A Python-based Retrieval-Augmented Generation (RAG) system for business insights using OpenAI GPT and FAISS. Ingests retail data, generates embeddings, and enables semantic search for financial, customer, and operational insights. Scalable API layer for real-time data-driven decision-making.

Retail AI Insights: Customer Intelligence with Hybrid ML

A machine learning project for customer segmentation using the DBSCAN density-based clustering algorithm on the Wholesale Customers dataset. The project identifies purchasing patterns, detects outliers, analyzes customer behavior, and visualizes cluster differences across spending categories.

AI-powered real-time people counting system using YOLOv8. Cross-platform desktop app for retail, restaurants, offices, and events. 100% offline, privacy-first.

Agentic ai based retail analytics dashboard

Retail analytics dashboard with guided tour, KPI tracking, and scenario simulations

AI-powered retail analytics platform that uses computer vision to track customer behavior, optimize store layouts, manage inventory, and provide personalized shopping recommendations using transformer architectures.

AI-Powered Sales Forecasting Dashboard (Future Interns ML Task 1) using Python, SARIMA, and Streamlit.

🛒🔍 PyTorch retail detective for spotting products on crowded shelves! Built for I2DL course using ResNet50 + FPN. Great for learning dense object detection, includes testing and YOLOv5 comparisons.

ML-powered retail layout optimizer using graph theory, clustering, and optimization algorithms. Built with Python, MySQL, Flask & NetworkX.

Production-grade Retail ETL & Analytics Pipeline — automated, monitored, and business-aware.