Paper Title
Airbnb Price Prediction using Machine Learning

Pricing online rental prices on Airbnb is a complex work for the owner and company. For companies, they need to process a large amount of new housing data every day, and for new landlords, they need a reasonable reference price and periodically improve the rental price. On the other hand, customers can be directly affected by price, so an appropriate price will increase the number of customers. This paper aims to develop a price prediction model using linear regression and machine learning to provide house owners and companies with a reference price, such as Ridge Regression and Random Forest. We use a large amount of data provided by Airbnb's shared rental platform, analyzes the rental information in the Boston area, and establishes an acceptable price prediction model by analyzing the data. Keywords - Airbnb, Price prediction model, Random Forest, Ridge regression