The backend of this feature uses a decision tree model trained on a real-world travel preferences dataset to recommend destinations. When users select their preferred season, activity type, budget, and continent on the frontend, the data is sent to a Flask API. The backend processes these inputs and predicts the most suitable travel destination along with a suggested activity. The recommendation is then returned and dynamically displayed on the frontend, helping users discover ideal locations tailored to their interests.
View the how the travel recommender works, step-by-step!