Fashionsta: Fashion Recommendations System

Abstract

Fashionsta is a modern, responsive fashion website designed to offer a seamless browsing experience and showcase a curated collection of trendy items. Built using HTML and CSS, the site features a sleek and user-friendly interface. Its responsive navigation menu ensures compatibility across all devices and screen sizes.

JavaScript and the Document Object Model (DOM) are used to implement dynamic elements such as product lists, category filters, and a search bar. JSON is utilized for efficient data exchange between the client and server. A key feature of Fashionsta is its integration of Machine Learning (ML) using the lightweight MobileNetV2 model. This enables smart outfit suggestions based on user preferences like skin tone and body type, enhancing personalization. The platform uses MongoDB, a NoSQL database, to store user and product data efficiently, maintaining performance even with growing data. APIs and HTTP protocols are employed to integrate external services, supporting features like payment processing and analytics. Fashionsta represents the blend of modern web development and fashion technology, delivering a customized and engaging online shopping experience.