Berlin Buzzwords 2017: Trevor Grant & Andrew Weiner - Real World AirBnB Data Science and Pricing Bot
Channel: Plain Schwarz
Date: 2020-02-13

For those getting started in AI, finding an interesting yet solvable problem can often be one of the greatest challenges. A project needs a set of data or stimuli that is rich yet easy to collect and a relevant problem that motivates the practitioner. If hoping to share the project with a diverse audience, it must not require extensive background industry knowledge. Data from Airbnb’s API is a “one-stop-shop” for new practitioners to experiment with a very diverse set of techniques and methods from the AI/Machine Learning canon. 

This tutorial introduces the Airbnb API, shows how to collect data from it, and presents a collection of examples of how artificial intelligence tools and algorithms can be used to extract value from the data.

This tutorial is motivated by the speaker’s own experience--he has a spare apartment and a guest apartment in the Logan Square neighborhood of Chicago that he began renting on Airbnb.  Trapped indoors throughout the savage Chicago winter, he spent his time building a bot that seeks to optimize the listing price and apartment description for his listing. The success of this project has led the speaker to consider purchasing another property in the neighboring Avondale neighborhood as an Airbnb investment property.

This tutorial will present the interesting highlights of the project, to include the following.

A Python script collects the listings available for each of the next 60 days.  Each listing has structured information such as the offered price, number of bedrooms, unit rating, host rating, etc. and unstructured information such as a title, description of the unit, and pictures.

Using Apache Spark, the JSON data is loaded into SparkSQL tables. Advanced querying techniques in SparkSQL are leveraged to convert semi-structured JSONs into structured tables for consumption by machine learning algorithms. Additional columns such as “rented units” and “price” are inferred if a unit was “available” yesterday, but is not listed today.

Read more:

About Trevor Grant:
https://2017.berlinbuzzwords.de/users/trevor-grant

About Andrew Weiner:
https://2017.berlinbuzzwords.de/users/andrew-weiner

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