Social networks are a treasure trove of publicly available data. Updated in real-time by contributors, this information can be used by public services to identify emergencies or disasters.
This project applies Natural Language Processing to vectorize tweets to enable subsequent machine learning algorithms to classify new data into disaster (1) or "normal" (0) tweets. The solutions are then deployed via flask and docker.
To see code and results, follow the link to my Github page.