Online Guest Lecture: Machine Learning & Deep Learning with ArcGIS

Learn about GeoAI workflows and the spatial applications of machine learning & deep learning from two Esri Solution Engineers. 

This guest lecture will introduce GeoAI workflows using ArcGIS, with a focus on machine learning and deep learning applications. The speakers will first provide a broad overview of GeoAI and explain how machine learning and deep learning fit within GIS workflows. They will discuss how machine learning can be used to predict spatial patterns from feature data and attributes, and how deep learning can be used to extract information from imagery, rasters, and point clouds.

The lecture will include examples of machine learning tools in ArcGIS Pro, such as classification, regression, and clustering, as well as deep learning workflows for image classification, object detection, semantic segmentation, and instance segmentation. The speakers will also briefly introduce how Python, ArcGIS Notebooks, and Deep Learning Studio can support automation, model training, and GIS-based prediction workflows.

Guest Speakers

Wynnie Gross is a Solution Engineer at Esri working at the intersection of geospatial technology, science, and public policy. She helps federal health and science agencies apply GIS to support environmental monitoring, scientific research, and public health missions. Her work focuses on spatial statistics, geospatial analytics, cartography, imagery, and remote sensing, with interests in environmental justice and urban planning. She holds a B.A. in Geography & Urban Studies and an M.S. in Geographic Information Science from Clark University.

Chris Jensen is a Defense Solution Engineer at Esri. His work focuses on helping organizations use GIS to transform spatial information into actionable insight, with experience related to defense and intelligence workflows, enterprise GIS solutions, imagery, and ArcGIS-based analysis.

Zoom link: Contact Xin Xu at @email or visit the Department Calendar.