🧠 A Streamlit web app that predicts Amazon sales amounts using a Multilayer Perceptron (MLP) model. Features real-time input, cleaned data, and a trained MLPRegressor with encoding and scaling pipelines.

This project aims to analyze e-commerce data to derive meaningful insights about customer behavior, sales trends, and product performance. We utilize Python, MySQL, and various data visualization libraries to perform the analysis.

An interactive interface for performing CRUD operations (Create, Read, Update, Delete) on a MySQL database related to Zomato data.

This repository contains a Power BI dashboard project focused on Amazon Sales Analytics. It provides insights into: Total sales and profit trends, Product category performance , Regional sales analysis, Customer segment insights .

Web scraping and analysis of sneaker listings from Amazon.sg to uncover pricing, brand strategy, and customer rating insights.

AI agent for answering SQL-based questions using LLaMA and FastAPI

End-to-end CRM analytics using cleaned eCommerce datasets to identify retention drivers, analyze funnels, and predict repurchase. Includes automated Python pipelines, logistic and linear modeling, and interactive Power BI dashboards for actionable business insights.

Customer segmentation for an online retail store using RFM analysis and K-Means clustering to identify distinct customer groups for targeted marketing.