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Responding to Earthquakes using Machine Learning and Racing through Time

Level:
intermediate
Room:
terrace 2b
Start:
Duration:
45 minutes

Abstract

Right after the devastating earthquakes in Turkey, there has been a massive flow of tweets and posts from survivors and their relatives, calling for help. There was a need to extract the data, make it meaningful and open to public, so we have come up with afetharita.com. The machine learning part of the application is completely based on open-source tools in Python and I will go through the pipeline and the process.

TalkPyData: Deep Learning, NLP, CV

Description

On February 6, 2023, earthquakes measuring 7.7 and 7.6 hit South Eastern Turkey, affecting 10 cities and resulting in more than 42,000 deaths and 120,000 injured as of February 21.

A few hours after the earthquake, a group of programmers started a Discord server to roll out an application called afetharita, literally meaning, disaster map. This application would serve search & rescue teams and volunteers to find survivors and bring them help. The need for such an app arose when survivors posted screenshots of texts with their addresses and what they needed (including rescue) on social media. Some survivors also tweeted what they needed so their relatives knew they were alive and that they need rescue. Needing to extract information from these tweets, we developed various applications to turn them into structured data and raced against time in developing and deploying these apps. The machine learning part of the application is completely based on open-source tools in Python and I will go through the pipeline and the process.


The speaker

Merve Noyan

Merve Noyan

I'm a developer advocacy engineer at Hugging Face and a natural language processing researcher. I'm also a Google Developer Expert in machine learning. You can find about my talks, blogs and more here: https://merveenoyan.github.io/me/


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