A modularized SDK library for Amazon Selling Partner API (fully typed in TypeScript)

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 data analysis project exploring consumer behavior and sales trends through EDA using Python. Includes visualizations and insights derived from retail shopping data.

This repository contains results of the completed tasks for the Quantium Data Analytics Virtual Experience Program by Forage, designed to replicate life in the Retail Analytics and Strategy team at Quantium, using Python.

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 Data Analysis project performing Exploratory Data Analysis (EDA) on Global Electronics' data to uncover insights that enhance customer satisfaction, optimize operations, and drive business growth.

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.

International electronics retail analysis across 15+ countries using 50K+ sales records | Power BI, SQL, Python, DAX, Interactive Dashboards

Implementation of a d3.js Visual Analytics dashboard for Sales Analysis and Customer Segmentation in Retail

AI-driven retail analytics platform with predictive inventory management, dynamic pricing, and marketing optimization for Walmart Sparkathon 2025

Analyse the customer purchase behaviour to optimize inventory cost

This project is based on supply chain analytics along with demand forecasting and inventory management of the top selling product. Demand forecasting is done by using the prophet time series model. Also, the dashboard consists of all the important insights related to customers, products, orders as well as the forecasting outcomes.

This project looks at the sales pattern of a product category in a retail store, using the store’s transaction dataset and identifying customer purchase behavior, to generate insights and recommendations.

RFM customer segmentation analysis of £17.7M retail dataset using K-means clustering and Python