As a part of this year's RBC Borealis AI Lets Solve It Program, I worked in a team setting to develop a research paper and deliverables for our topic on utilizing deep learning for earthquake detection.
The process for the program was a written application submission on our chosen project and then an interview with a member of the Borealis AI team to understand our project's benefits, how we were planning to implement it and answer any other logistical questions.
The project was inspired by our group's passion for environmental sustainability and learning more about natural disasters and how we can better detect them to help with disaster mitigation and education or awareness efforts.
We worked over the course of a few months as a group to plan out the deliverables, which included the white paper and presentation to RBC Borealis AI ML engineers and mentors who helped organize the program over the term.
The program was helpful in that we were able to get weekly mentorship from ML engineers who were able to give us guidance on how to improve the model, and resolve any potential technical difficulties, and there were also workshops on how to make a good pitch and resources on intro to ML.
Tt was really inspiring to learn from the other teams as well at the end of the presentation.
I'm thankful to the RBC Borealis AI team for this opportunity!
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