Paper Contents
Abstract
A web-based e-commerce application called OnlineShoppingML was created to offer a streamlined, safe, and customised purchasing experience. The system, which was created with Python 3.x, Flask, and SQLite, allows users to sign up, log in, explore products, add items to a shopping cart, and place orders. Administrators can effectively manage products and transactions. The use of machine learning-based product suggestions, which improve customer engagement by making pertinent item recommendations based on browsing and purchase history, is a crucial component of the system. With a focus on security, scalability, and usability, the project shows how web technologies and intelligent systems may be used practically in contemporary e-commerce.1.INTRODUCTIONA machine learning recommendation system has been added to OnlineShoppingML, a web-based e-commerce application created with Flask and SQLite. It is meant to mimic an actual online store where customers can explore merchandise, control their shopping carts, place and monitor orders, and get tailored product recommendations. The project demonstrates how machine learning may be incorporated into real-world applications like e-commerce and also acts as a teaching tool for web development using Flask.All of the essential features of a contemporary online shopping platform are offered by the program. With Flask- Login, users can create accounts, log in, and manage their profiles while maintaining secure access. While the shopping cart system enables the addition, deletion, and updating of items, the product catalogue facilitates browsing and searching. Customers may place orders, check the status of their transactions, and even obtain invoices in PDF format after making a purchase.
Copyright
Copyright © 2025 Shubha H M. This is an open access article distributed under the Creative Commons Attribution License.
