Machine Learning-Based Cluster Analysis Workshop 

This event is part of the Harvard Affiliate Only Spatial Data Science Workshop Series.
January 28, 2022 | 12:00 PM ET
Course Description:
Machine learning can play a critical role in spatial problem solving in a wide range of areas, including spatial pattern detection. The ability to automate this type of pattern detection is crucial when addressing the world’s most challenging spatial problems. This workshop covers machine learning methods to perform cluster analysis using attributes, space, and time. We'll cover methods such as Multivariate Clustering, Build Balanced Zones, and Density-based Clustering in both space and time. Each technique is explained in conceptual terms to understand how it works and accompanied by a demonstration that showcases its use. Use cases will include climate and environmental data, data for social good, and more.
Prior to the workshop attendees will be provided an ArcGIS Pro project with demo data that will be used throughout the workshop. Attendees will be invited to follow along during demonstrations using the provided data, though this is not required.
Panelists:
Lauren Bennett
Alberto Nieto
Ankita Bakshi

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