Machine Learning for Smart Cities 1.0

"How are smart cities solving everyday urban problems with machine learning algorithms and big data?"

City governments are increasingly using Machine Learning (ML) methods to help serve their citizens better. This workshop provides World Bank staff with an understanding of the nuts-and-bolts of ML in a smart city context.

Focused on a simple, but powerful family o... view more


Welcoming Remarks: Hyoung Gun Wang, Senior Economist & Smart Cities KSB Lead at the World Bank Group, introduces (1) Jon Kastelan, a Machine Learning Specialist and (2) Nick Jones, a DRM Specialist at the World Bank Group.


Presentation Part 1: Nick Jones and Jon Kastelan introduce different families of machine learning algorithms, and walk learners through a business case study entailing their application.


Presentation Part 2: Nick Jones and Jon Kastelan teach basic aspects of machine learning applications, such as (1) obtaining data, (2) designing predictive features, and (3) handling training and test data.


Presentation Part 3: Nick Jones and Jon Kastelan walk through the basics of evaluating and then deploying a machine learning model.


Presentation Part 4: Nick Jones and Jon Kastelan moderate a group exercises to brainstorm possible uses of machine learning within different smart city cases.

About the Presenters

Jon Kastelan

Jon Kastelan, Machine Learning Specialist, has advised governments and city agencies on analytics and machine learning across North America and Asia Pacific. He worked with PwC's Analytics and Urbanisation practice to support development of the Smart City blueprint for Hong Kong. He has also taught data science and analytics at New York University and worked with urban-focused start-ups.

Nick Jones

Nick Jones, DRM Specialist at GFDRR, spent 2017-2018 as a CUSP Fellow at New York University. He led a graduate seminar program on urban data analysis, and worked on data science methods at the NYC Department of Buildings and Mayor’s Office of Data Analytics.