Projects
A curated selection of web development and data analytics projects showcasing skills in full-stack development, data visualization, and real-world problem-solving using modern technologies.
Featured Projects
Sentiment-Based Music Recommender App
This cross-platform mobile application provides personalized song recommendations by analyzing the emotional sentiment of lyrics. Built using Expo (React Native), it allows users to either search for lyrics by artist and song name, or directly input custom text that reflects their mood or thoughts.The app uses the VADER sentiment analysis tool to evaluate the emotional tone of the input and calculates a sentiment score in real time. It then fetches songs with similar sentiment profiles from a pre-analyzed dataset stored in Firebase Realtime Database.By combining natural language processing with music discovery, the system offers a unique approach to music recommendation—matching users with songs that align with how they feel, rather than just what they have listened to before.
Order-Fulfilment-Database-for-an-E-Commerce-Platform
Designed to support a retail business expanding into the e-commerce space, this relational database models the core operations necessary for efficient online order management. It handles product catalog organization, customer orders, inventory tracking, and fulfilment processes across multiple UK-based warehouse To optimize delivery speed—following an Amazon-style model—the system intelligently links customer orders with the nearest warehouse that has the required items in stock. It incorporates real-world logistics features such as postcode-based warehouse coverage, delivery time estimation, and stock allocation logic.The implementation showcases strong relational design, including normalized schema structures, many-to-many relationships, and advanced SQL logic to reflect practical business operations in a scalable and efficient manner.
Predicting Hotel Booking Cancellations with Machine Learning
Hotel booking cancellations at the last minute can cause serious problems for hotel staff, including overstaffing, wasted resources, and lost income. This project uses machine learning to help predict which bookings are likely to be cancelled, so hotels can plan better and reduce losses.By analyzing past booking data—such as how early the reservation was made, the type of customer, length of stay, and whether special requests were included—the system learns to identify useful patterns. It then uses this information to predict whether a new booking might be cancelled in advance.The goal is to help hotels make smarter decisions, improve customer service, reduce financial risk, and manage room availability more efficiently.
Music Library App
This cross-platform mobile prototype is a Music Library App designed for both iOS and Android using a modern and user-friendly interface. The app allows users to search, explore, save, and share their favorite music albums in a smooth and intuitive experience.Developed to showcase core mobile development concepts, the project integrates external music APIs to fetch real-time album and artist data. It also supports local data storage, enabling users to save albums for offline access, and includes social media sharing features to let users share their musical tastes with friends.The project demonstrates clean UI design principles, practical use of API integration, data persistence, and cross-platform compatibility. It serves as a functional prototype of a personalized music discovery and curation experience on mobile devices..
Environmental Sustainability Ontology
This project applies Semantic Web technologies to model and understand the complex relationships between human activities and environmental sustainability. Using OWL (Web Ontology Language) and RDF (Resource Description Framework), the system represents structured knowledge about how actions such as urban development, agriculture, and industry impact natural ecosystems over time.The goal is to create a flexible, machine-readable knowledge base that enables reasoning, data linking, and semantic querying across various environmental contexts. It supports use cases such as policy modeling, sustainable planning, and environmental impact analysis by capturing intricate cause-and-effect relationships between socio-economic behaviors and ecological consequences.This project demonstrates practical skills in ontology engineering, semantic data modeling, and knowledge representation, contributing to a more intelligent and interoperable framework for understanding sustainability challenges..