in Syracuse, New York
A Data-Driven Aproach to Code Inspections
Scott Betz - Jibran Khan - Jonathan Yuan
This project is culmination of a semester-long graduate practicum course in urban spatial analytics (MUSA801) in the Department of City & Regional Planning at the University of Pennsylvania taught by Ken Steif, Matthew Harris, and Michael Fichman. Click here to return to MUSA website to view other projects. The work was complete as a proof-of-concept for the City of Syracuse Innovation Team. All of the methods are posted within and are open-sourced with the intent that the research will help other interested municipalities in creating their own prediction tool. For additional information on this work, please email one of the project team members.
ScottDBetz@gmail.com | jibran.n.khan@gmail.com | jyuan@nyu.edu
This document begins with a case study predicting risk of health & safety code violations in homes in Syracuse, New York, and is followed by a series of appendices that discuss data wrangling, data visualization, data sources, feature engineering, and model results. Navigate through the document either by using the panel at the left, or by clicking the hyperlinks throughout the document.