By Banan Alhethlool | banan.alhethlool@gmail.com
The second project for Data science Bootcamp T5 on Regression. Through the project by building a machine learning linear regression model, we will shed light on the company that we study to assist with their issue, dataset description, and finally, the tools used in this project.
Airbnb, Inc. is an American company that operates an online marketplace for lodging, primarily homestays for vacation rentals, and tourism activities. The platform is accessible via website and mobile app.
Many hosts do not know how to price their properties, sometimes it is not appropriate for the services provided, whether the price is high or low. We will make price predictions based on the services provided to help hosts determine the right price.
The data service will predict the realistic pricing for hosts products; it helps the hosts to price their appropriate, and the Airbnb to have prices suits the platform users.
The used dataset scraped from airbnb.com with 10 features and 522 rows will be helpful for the study. Sample size is 5 major cities (London, Milano, Berlin, Madrid and Amsterdam) that are located in the continent of Europe.
- Technologies: Jupyter Notebook, Python.
- Libraries: Pandas, NumPy, Matplotlib, Seaborn, BeautifulSoup and Selenium.