This is an effort to understand 77 different designated neighborhoods of Chicago using public datasets. The datasets can be classified under three major categories.
- Residential - Median rental price, Short term rental data (price, availability) through Airbnb listing data
- Accessibility - Public transportation options, bikeshare data & travel time to downtown using Google Map API
- Quality - Number of restaurants, park-recreations coverage, crime data
After augmenting these datasets on Neighborhood level, an unsupervised learning model is used to classify these Neighborhood into similar groups. Read more
I shall be writing an elaborate post on the work very soon.