Meili is an application that creates a trip itinerary for users based on their preferences and historical data on what similar users have enjoyed.
- Project Owner: Roman Gorelik
- Scrum Master: Erik Lin
- Team Members: Guillermo Adrian, Martin Glyer
- Google and Facebook sign up and log in.
- Dynamic splash page allowing users to seamlessly transition around the page.
- Drag and drop activities or days.
- View up to date graphs representing user spending budget.
- View past and current trips in user profile, with ability to download PDF of the current trip.
- Quick onboarding process to allow better user recommendations.
- Recommendations change based on weather prediction.
- Leveraged IBM Watson NLP and Microsoft Azure to categorize activities based on their description and images, respectively.
- Implemented Recombee, a lazy variant of rule-based recommmendation systems, to give user recommendations.
- Created weather prediction model using Prophet for weather-based recommendations.
