Reef Life Survey

Lessons learned building a fish ID web app with fast.ai and Streamlit, in an attempt to reduce my fear of missing out on the latest deep learning developments.

My track record of posting here has been pretty poor in 2020, partly because of a bunch of content I’ve contributed elsewhere. In general, my guiding principle for posting is to only add stuff I’d want to read or cite, e.g., because I haven’t seen it discussed elsewhere. Well, no one has compiled a meta-post of my public work from 2020 (that I know of), so it’s finally time to publish it myself....

Last year, I wrote about the Reef Life Survey (RLS) project and my experience with offline data collection on the Great Barrier Reef. I found that using auto-generated flashcards with an increasing level of difficulty is a good way to memorise marine species. Since publishing that post, I have improved the flashcards and built a tool for exploring the aggregate survey data. Both tools are now publicly available on the RLS website....

Many modern data scientists don’t get to experience data collection in the offline world. Recently, I spent a month sailing down the northern Great Barrier Reef, collecting data for the Reef Life Survey project. In addition to being a great diving experience, the trip helped me obtain general insights on data collection and machine learning, which are shared in this article. The Reef Life Survey project Reef Life Survey (RLS) is a citizen scientist project, led by a team from the University of Tasmania....