Tourism Africa

Discovering suitable travel destinations in Africa can be overwhelming due to fragmented information and the lack of intelligent, personalized recommendation systems tailored to diverse traveler interests.

Tourism Africa is a web-based platform that uses a custom-built machine learning recommendation system to match users with African travel destinations based on their preferences and destination-specific features. The platform combines a modern web interface with a Python-based backend and a bespoke ML model designed specifically for tourism discovery.

• Designed and built the full web application end-to-end
• Developed the frontend using Next.js
• Built the backend API using FastAPI and Python
• Collected, cleaned, and structured tourism-related data from multiple sources
• Designed and implemented a custom machine learning recommendation system
• Engineered features combining user preferences with destination attributes
• Trained and evaluated the ML model to improve recommendation relevance
• Integrated the ML model into the backend API for real-time recommendations
• Designed and managed the PostgreSQL database hosted on Neon
• Handled deployment and environment configuration

• Personalized destination recommendations powered by a custom ML model
• Preference-based matching between users and travel destinations
• Structured destination data enriched with feature engineering
• API-driven recommendation flow between frontend and backend
• Clean and intuitive UI for exploring African tourism destinations

• Designing an effective recommendation algorithm without relying on off-the-shelf models
• Collecting and normalizing diverse tourism data across multiple destinations
• Balancing recommendation accuracy with performance for real-time responses
• Integrating machine learning workflows into a production-ready web application