Data Science2021Data Scientist

East-Central London & Birmingham Venues

IBM Data Science Professional Certificate capstone

Compared East-Central London and Birmingham by venue category using Foursquare, geolocation, Folium maps, and K-means clustering (6 clusters in ECL, 2 in Birmingham).

The Problem & Engineering Constraint

The Core Challenge

Neighbourhood comparison is noisy if you only look at raw venue counts. The brief needed cleaned data, maps, and unsupervised structure.
Technical Architecture & Approach

Engineering Solution & Implementation

Pandas cleaning, Matplotlib visualisation, Folium + Foursquare + Geolocator APIs, then scikit-learn K-means. Discussed how venue-category clusters apply to each city.

View repository on GitHub

Measured Production Impact

Verified Outcomes & Deliverables

Formed 6 venue clusters in East-Central London and 2 in Birmingham.

Capstone for the IBM Data Science Professional Certificate.

Technologies & Components

System Tooling & Technologies

PythonPandasFoliumFoursquare APIGeolocatorScikit-LearnK-means