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.

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

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

DataSpark is a data analysis project using Python, SQL, and Power BI to analyze global electronics retail sales, focusing on customer behavior, sales performance, product profitability, and store performance to optimize sales strategies.

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.

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

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]

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

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.

Analyse the customer purchase behaviour to optimize inventory cost

Solution to Quantium Virtual Internships on Forage

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