Using EOLearn to build a machine learning pipeline to detect plastics in the ocean.
The past 10 years has seen an explosion of data from remote sensing satellites.This data, which can be used for a wide range of applications, can be hard to obtain and use. EOLearn aims to bridge the gap between the remote sensing and machine learning world. In this talk, we will discuss how to build a ML remote sensing pipeline in python using an ocean plastic detection project as an example.
Stuart Lynn is the data science lead at the Data Clinic where he helps nonprofits use data to better serve their communities, conducts independent research and develops new tooling that enhances the use of open data.
Stuart is a firm believer that access to good data and tools can be a game-changer, having previously spent 6 years working at the Zooniverse, the world’s largest collection of online citizen science projects, and also headed up data science at CARTO, a company that specializes in making spatial data and analysis accessible.
Stuart holds a PhD in Astrophysics and a Masters in Mathematical Physics from the University of Edinburgh. When not working at Data Clinic you can find Stuart buried in his side projects, including building tools to explore historic maps, creative coding and tinkering with hardware.