Data Science project to create a price estimation tool for Airbnb listings
Group Members : Ajay Anand, Jiong Chen, Jiayu Li
Data Sources: “Airbnb Price New York City” from Kaggle.com. The “Airbnb Price New York” dataset contains information regarding rentals around the New York city area. The data contains the basic information regarding the rentals, the basic information, tiers, and reviews regarding the hosts, and also corresponding pricing information. The dataset was introduced and shared by Jiayu Li’s friend from Columbia University.
Study Aim: The project aims to study the correlation between the rental sales price with variables including but limited to host tiers, location, rental types and dimensions, beds types, and the sales (listing) price of the rental on Airbnb, which is a large rental marketspace operating worldwide. After that, our group aims to predict the list price using different machine learning models and apply a proper neural network model which will be referenced by hosts and potential renters for specific properties.
Ultimate Objective: The ultimate objective of this project is to testify and predict the proper price for a specific rental, which can benefit both the hosts and potential renters. Both regression for price prediction and classification regarding below or above average has been conducted in this proejct. Our group hopes to help the hosts to understand proper range for their properties and adjust their listing price accordingly to increase reservation rate. Also, our group also hopes to use the models and results to help potential renters to understand the listing price for a specific property they are interested in.
This blog post explains the background of post but uses a different dataset:https://towardsdatascience.com/predicting-airbnb-prices-with-machine-learning-and-deep-learning-f46d44afb8a6