This project is a part of University of Maryland's BUDT 758T Class Project. It is a class-wide Kaggle like contest to predict whether an Airbnb.com listing will have a high booking rate. The winning team will achieve the highest AUC for the test instances. My project got the second highest AUC of 0.916 on the hidden dataset.

Airbnb High Booking Rate Prediction

Airbnb, Inc. is an american vacation rental online marketplace company based in San Francisco, California, United States. Airbnb offers arrangement for lodging, primarily homestays, or tourism experiences. The company does not own any of the real estate listings, nor does it host events; it acts as a broker, receiving commissions from each booking. In this project we are trying to predict whether a listing would receive high booking or not.

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Project focussing on in-depth data analysis of Airbnb Chicago dataset and a prediction model to help investors choose the best property that would result in a high booking rate. Specifics of Chicago market have been analyzed in detail.

The aim of this predictive model is to forecast high booking rates for Airbnb listings. Leveraging a boosting model that incorporates diverse property and host-related variables, this model is designed to provide hosts and property managers with precise predictions that can inform strategic decisions and optimize property performance.