This capstone project was created as part of the Eskwelabs Data Science Fellowship Cohort VI.

Visit the web application for this project here: https://airbnbphpricing.herokuapp.com/

Check the pdf file here: https://bit.ly/3eWqjUq

Last year, as with most other businesses, Airbnb was rocked by COVID-19. Multiple news about Airbnb's future headlined several articles as large numbers of cancellations and slow bookings created a massive loss in revenue globally but even more appalling is the situation of its hosts.

With the current situation, the collapse of startups has been prevalent during the pandemic. Airbnb experienced a booking drop over 70% and cut its half in valuation.

In the wake of the pandemic, emergence of dynamic pricing has become a business strategy for survival.

1. To identify the factors affecting the price of Airbnb listings in the Philippines.

2. To train a machine learning model that identifies a pricing system for PH Airbnb hosts to optimize their listing price.

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https://www.linkedin.com/in/edward-apostol/

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https://www.linkedin.com/in/tyronrexfrago/

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https://www.linkedin.com/in/lunazipporahd/

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https://www.linkedin.com/in/jonarie-vergara/

[email protected]
https://www.linkedin.com/in/johnbarrion/