Price prediction for Melbourne Airbnb listings

Hosts on Airbnb often end up using a trial and error approach or have to perform an extensive market analysis to come up with a sensible price for their property. A helpful recommendation that Airbnb can provide is an approximate range of price based on similar properties hosted by others. Melbourne Airbnb dataset was used to perform predictive analysis of price of listings using Supervised Machine learning. Regression models were built and hyperparameters tuned using 5 fold cross validation. XGBoost Regressor gave a significantly higher performance with a Root Mean Squared error (RMSE) of 48.1 over a Naive baseline model (RMSE 75.8).