Satellite Imagery To Make ML Models

How to use Satellite Imagery to be a Machine Learning Mantis Shrimp

Presented By Sean Patrick Gorman, PhD & Steven Pousty
Sean Patrick Gorman, PhD & Steven Pousty
Sean Patrick Gorman, PhD & Steven Pousty

Sean is the Head of Technical Product Management at DigitalGlobe helping build GBDX and next generation machine learning tools for satellite imagery. Sean received his PhD from George Mason University as the Provost's High Potential Research Candidate, Fisher Prize winner and an INFORMS Dissertation Prize recipient

Steve is the Developer Relations lead for DigitalGlobe. He goes around and shows off all the great work the DigitalGlobe engineers do. Steve has a Ph.D. in Ecology from University of Connecticut.

Presentation Description

In this session we are going to start by showing you how satellite imagery actually allows you to “see” in more bands of color than the mantis (how about 26 bands) – each band is a massive amount of data about the earth. We will show you how you can work with this data in Jupyter notebooks to extract all sorts of information about the world. Last, we will wrap up with how to make ML models using this data, extract features we care about, and then run it through a cloud-based processing model.

Presentation Curriculum

How to use Satellite Imagery to be a Machine Learning Mantis Shrimp
31:18
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