This project was developed for the Rootcode Datathon, featuring a content-based filtering machine learning model designed to recommend the best travel locations for tourists visiting Sri Lanka. The model takes into account user preferences and bucket list destinations to offer personalized recommendations.
- Personalized Travel Recommendations: The model tailors travel suggestions based on user inputs such as preferred activities and desired locations.
- Content-Based Filtering: Using a content-based approach, the model compares user preferences to a curated database of Sri Lankan travel destinations.
- Ratings and Prioritization: Destinations are ranked and prioritized not only by how well they fit the user’s preferences but also based on location ratings and reviews.
- Bucket List Integration: The model gives higher priority to locations listed in the user's bucket list for a more tailored experience.
- Data-Driven Insights: Additional metrics such as user ratings and reviews are provided to help users make informed decisions.
- Python
- Scikit-learn (TfidfVectorizer, Cosine Similarity)
- Pandas
- Matplotlib & Seaborn (for visualization)
- Pickle (for model saving/loading)
This project aims to enhance the travel experience for tourists by offering well-rated and highly relevant travel destination suggestions across Sri Lanka.