This past Thursday we were really lucky to catch Dani Arribas-Bel, Senior Lecturer in Geographic Data Science at the University of Liverpool and major contributor to PySAL, on his way back home following two weeks’ […]
Although it has taken rather a long time to see the light of day, our just-published paper is one of the reasons I love my job: drawing on a mix of data science and deep geographical knowledge, we look at the role that new Machine Learning (ML) techniques – normally seen as just a ‘black box’ for making predictions – can play in helping us to develop a deeper understanding of gentrification and neighbourhood change. For those of a ‘TL;DR’ nature (or without the privilege of an institutional subscription!), we wanted to share some of our key ideas in a more accessible format.
We’re really pleased to announce that on Wednesday, 22 February Professor Sergio Rey, of the School of Geographical Sciences and Urban Planning at Arizona State University will be discussing the Python Spatial Analysis Library (PySAL). […]