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.