KalyanM45/End-to-End-Airbnb-Price-Prediction
The purpose of this project is to predict the price of Airbnb rentals based on various features of the properties listed on the platform. The code in this repository is written in Python and uses several machine learning algorithms to train and test a predictive model.
Implements an end-to-end ML pipeline combining XGBoost and CatBoost for price regression, with DVC for experiment tracking and reproducibility. Exposes predictions through a Flask web API and provides containerized deployment via Docker, enabling both local development and production scaling. Leverages ensemble methods across location, property type, and market features to balance host revenue optimization with guest affordability.
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Last pushed
Dec 13, 2023
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