Come learn about some of the most widely adopted machine learning methods used for clustering of spatial data. This forum will illustrate how the algorithms work, how to interpret the results, and how and when to apply them.  We’ll go beyond the basics of several key spatial data science techniques, including density-based clustering and multivariate clustering, and equip you with the knowledge necessary to do great analysis.

About the speakers

Lauren Bennett leads the Spatial Analysis and Data Science software development team at Esri. In this role, she oversees the R&D of the ArcGIS analytical framework, which includes spatial and spatiotemporal statistics, raster and multidimensional analysis, machine learning and big data analytics. She directs releases of new spatial data science capabilities across a wide range of products and applications including desktop, enterprise and SaaS. Lauren received a BA in Geography from McGill University, an MS in Geographic and Cartographic Science from George Mason University, and her PhD in Information Systems and Technology from Claremont Graduate University.

Ankita Bakshi is a Senior Product Engineer for the Spatial Statistics Team at Esri. With a background in environmental engineering and computer science, Ankita loves doing the investigative work of finding patterns in the data. She is passionate about providing solutions for social, economic, racial and environmental challenges using Spatial Analysis and Data Science. In her role, Ankita enjoys researching, finding software solutions, and creating video and written content to make the data analysis tools more approachable and applicable to real world challenges. Outside of work Ankita enjoys going on hikes, painting landscapes, dancing and listening to Bollywood music.