This repository houses the machine learning models and services that power Trexense, our AI powered travel planner app.
The Trexense ML Repository consists of three key sub-repositories, each serving a unique purpose in our ML pipeline:
- Repository:
recommendation-system - Description: Develops a content based filtering hotel recommendation system using TensorFlow. This system leverages user activity data to suggest personalized hotel options.
- Repository:
ml-auto-itinerary-chatbot - Description: Utilizes Vertex AI to build a chatbot capable of generating custom itineraries based on user queries.
- Repository:
ml-server - Description: Handles the deployment of all our machine learning features using Flask, serving the recommendation system and chatbot as production-ready APIs. This repository ensures that the models are accessible and scalable for real-time use.